3,157 results on '"fuzzy model"'
Search Results
2. Systematic Planning and Early-Stage Development of Industrial AI Systems for Plant Optimization
- Author
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Voigt, Jorrit, Gillmann, Marlene Judith, Dröder, Klaus, Open Hybrid LabFactory e.V., Dröder, Klaus, editor, and Vietor, Thomas, editor
- Published
- 2025
- Full Text
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3. Analysis of Modeling Organizational and Technical Factors of Operation in a Fuzzy Formulation.
- Author
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Smirnov, A. V., Brom, A. E., and Sidel'nikov, I. D.
- Abstract
The article systematizes the factors influencing reliability, identifies the failure rate at the operating stage for research, and proposes a fuzzy model for correcting the failure rate, taking into account the influence of real factors during operation. The results were tested on a Siemens-SGT-800 gas turbine. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
4. Next-Generation Building Condition Assessment: BIM and Neural Network Integration.
- Author
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Amrouni Hosseini, Mani, Ravanshadnia, Mehdi, Rahimzadegan, Majid, and Ramezani, Saeed
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ARTIFICIAL neural networks , *CONSTRUCTION management , *CONSTRUCTION defects (Buildings) , *OFFICE buildings , *BUILDING information modeling - Abstract
The inspection of building components plays a crucial role in reducing maintenance costs throughout the building's life cycle. Many buildings suffer from defects in the building elements, such as surface problems, cracks, and moisture problems. Building Information Modeling (BIM) has become a widely used digital tool for the construction industry, allowing for the virtual visualization, design, and simulation of structures. At the same time, progress in neural networks, a branch of artificial intelligence, presents encouraging potential for classification and evaluation. This article explores the fusion of BIM and neural networks to improve and simplify the building inspection procedure. Neural networks are implemented with BIM to conduct real-time analysis and predictions as part of an inspection framework. A data set consisting of 500 wall samples with defects from different buildings was collected through fieldwork. These data were then classified into five categories, ranging from D1 (No damage) to D5 (Collapse), based on expert opinions. A neural network was used to create a model that can show the severity of degradation of building elements. The BIM platform is utilized in the implementation of the proposed model to facilitate the exchange of information and enhance documentation during inspection. The visualization provided by BIM allows the facility management team and building owners to assess building elements through causality analysis using distinct color codes. A case study of an office building is featured in the paper to showcase the application of the proposed model for asset management. The color-coded system used in this study denotes low-performance conditions as red, medium performance conditions as yellow, and high-performance conditions as green. This article outlines the procedures for categorizing and ranking defects in building elements, specifically focusing on walls. Practical Applications: This study explores innovative methods for assessing the condition of buildings, aiming to improve accuracy, efficiency, and predictive capabilities. Traditional building inspections are often subjective, time-consuming, and labor-intensive, making it challenging to generate consistent and comprehensive evaluations. Our research addresses these limitations by integrating BIM and neural networks. BIM provides detailed digital models of buildings, which include comprehensive information about each component. This technology enables precise and consistent assessments, reducing the subjectivity inherent in manual inspections. Neural networks, a type of artificial intelligence, can analyze complex data patterns and detect potential issues early, allowing for proactive maintenance. By combining these two technologies, our approach offers a more efficient and objective method for building condition assessment. This integration not only saves time and resources but also enhances the ability to predict and prevent future issues, ultimately extending the lifespan of building components and improving overall building performance. These advancements are particularly relevant for property managers, maintenance teams, and construction professionals seeking to optimize building maintenance and management practices. The findings of this study can significantly benefit the construction and facilities management industries by providing a more reliable and advanced method for maintaining building health and safety, thereby ensuring sustainable and cost-effective building management. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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5. Fractional Caputo Operator and Takagi–Sugeno Fuzzy Modeling to Diabetes Analysis.
- Author
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Mustapha, Ez-zaiym, Abdellatif, El Ouissari, Karim, El Moutaouakil, and Ahmed, Aberqi
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ARTIFICIAL intelligence , *DYNAMICAL systems , *DIABETES - Abstract
Diabetes is becoming more and more dangerous, and the effects continue to grow due to the population's ignorance of the seriousness of this phenomenon. The studies that have been carried out have not been able to follow the phenomenon more precisely, which has led to the use of the fractional derivative tool, which has a very great capability to study real problems and phenomena but is somewhat limited on nonlinear models. In this work, we will develop a new fractional derivative model of a diabetic population, the Takagi–Sugeno fractional fuzzy model, which will enable us to study the phenomenon with these nonlinear terms in order to obtain greater precision in the results. We will study the existence and uniqueness of the solution using the Lipschizian theorem and then turn to the new fuzzy model, which leads us to four dynamical systems. The interpretation results show the quality of fuzzy membership in tracking the malleable phenomena of nonlinear terms existing in the system. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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6. Solving the Problem of Fuzzy Partition-Distribution with Determination of the Location of Subset Centers.
- Author
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Bulat, Anatoly, Kiseleva, Elena, Yakovlev, Sergiy, Prytomanova, Olga, and Lebediev, Danylo
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MATHEMATICAL programming ,ARTIFICIAL intelligence ,MATHEMATICAL models ,INDUSTRIAL costs ,FUZZY algorithms ,MEMBERSHIP functions (Fuzzy logic) - Abstract
A large number of real-world problems from various fields of human activity can be reduced to optimal partitioning-allocation problems with the purpose of minimizing the partitioning quality criterion. A typical representative of such problem is an infinite-dimensional transportation problem and more generalized problems—infinite-dimensional problems of production centers placement along with the partitioning of the area of continuously distributed consumers with the purpose of minimizing transportation and production costs. The relevant problems are characterized by some kind of uncertainty level of a not-probabilistic nature. A method is proposed to solve an optimal fuzzy partitioning-allocation problem with the subsets centers placement for sets of n-dimensional Euclidean space. The method is based on the synthesis of the methods of fuzzy theory and optimal partitioning-allocation theory, which is a new science field in infinite-dimensional mathematical programming with Boolean variables. A theorem was proved that determines the form of the optimal solution of the corresponding optimal fuzzy partitioning-allocation problem with the subsets centers placement for sets of n-dimensional Euclidean space. An algorithm for solving fuzzy partitioning-allocation problems is proposed, which is based on the proved theorem and on a variant of Shor's r-algorithm—a non-differential optimization method. The application of the proposed method is demonstrated on model tasks, where the coefficient of mistrust is integrated to interpret the obtained result—the minimum value of the membership function, which allows each point of the set partition to be assigned to a specific fuzzy subset. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Monitoring and preservation of stone cultural heritage using a fuzzy model for predicting salt crystallisation damage
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Marta Cappai, Marta Casti, and Giorgio Pia
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Degradation kinetics ,Fuzzy model ,Multivariable approach ,Salt crystallisation ,Stone materials ,Medicine ,Science - Abstract
Abstract In this study, a fuzzy model is presented for predicting the possibility of degradation due to salt crystallisation cycles. The formalization of the proposed model has been based on the multivariable approach which considers environmental data (such as temperature, solar radiation, wind speed, rain quantity, relative humidity), characteristic inflection points of specific salts and stone features derived from laboratory characterizations (including mechanical properties, porosity, and mineralogical composition). Modeling results have been compared with experimental data elaborations acquired by monitoring a semi-confined archaeological site situated in the city of Cagliari (Munatius Irenaus cubicle), revealing substantial alignment in the degradation kinetics trends. Moreover, the achieved outcomes show the remarkable capability to identify salt crystallisation phenomenon type (efflorescence or subflorescence).
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- 2024
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8. New hybrid model for nonlinear systems via Takagi-Sugeno fuzzy approach
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Anouar Ben Mabrouk, Abdulaziz Alanazi, Zaid Bassfar, and Dalal Alanazi
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control ,dynamical systems ,nonlinear systems ,fuzzy model ,wavelets ,lyapunov stability ,Mathematics ,QA1-939 - Abstract
Mathematical models, especially complex nonlinear systems, are always difficult to analyze and synthesize, and researchers need effective and suitable control methods to address these issues. In the present work, we proposed a hybrid method that combines the well-known Takagi-Sugeno fuzzy model with wavelet decomposition to investigate nonlinear systems characterized by the presence of mixed nonlinearities. Here, one nonlinearity is super-linear and convex, and other is sub-linear, concave, and singular at zero, which leads to difficulties in the analysis, as is known in PDE theory. Linear and polynomial fuzzy models were combined with wavelets to ensure an improvement in both methods for investigating such problems. The results showed a high performance compared with existing methods via error estimates and Lyapunov theory of stability. The model was applied to a prototype nonlinear Schrödinger dynamical system.
- Published
- 2024
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9. Assessment of the industrial policy to the military-industrial complex effectiveness based on neural networks based on fuzzy logic
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E.N. Starikov, N.V. Klein, and V.I. Vorobyov
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industrial policy ,military-industrial complex ,efficiency ,evaluation indicators ,methodological approach ,fuzzy logic ,neural network ,fuzzy model ,Home economics ,TX1-1110 ,Economics as a science ,HB71-74 - Abstract
The relevance of the topic under consideration on the development of universal applied methods for assessing the effectiveness and efficiency of industrial policy in the military-industrial complex (hereinafter - MIC) is due to its high practical significance in the context of the challenges of technological development associated with digitalization and informatization. It is also due to the peculiarities of the current stage of Russia’s economic development in the conditions of financial and technological sanctions from Western states. The purpose of the study is to develop the main provisions of a methodological approach to assessing the effectiveness of industrial policy in the defense industry based on the use of economic-mathematical modeling apparatus, which involves the construction of neural networks based on fuzzy logic. In the course of the research the authors have solved the following problems: mathematically formalized the object of analysis; developed an algorithm for determining the effectiveness of industrial policy in the MIC using neural networks; formalized the model for assessing the effectiveness of such industrial policy based on fuzzy sets; proposed a system of indicators for assessing industrial policy in the MIC; determined the sequence of actions in the construction the fuzzy model for assessing the effectiveness of industrial policy in the MIC by means of Fuzzy Logic on the software platform MatLab.
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- 2024
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10. Monitoring and preservation of stone cultural heritage using a fuzzy model for predicting salt crystallisation damage.
- Author
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Cappai, Marta, Casti, Marta, and Pia, Giorgio
- Abstract
In this study, a fuzzy model is presented for predicting the possibility of degradation due to salt crystallisation cycles. The formalization of the proposed model has been based on the multivariable approach which considers environmental data (such as temperature, solar radiation, wind speed, rain quantity, relative humidity), characteristic inflection points of specific salts and stone features derived from laboratory characterizations (including mechanical properties, porosity, and mineralogical composition). Modeling results have been compared with experimental data elaborations acquired by monitoring a semi-confined archaeological site situated in the city of Cagliari (Munatius Irenaus cubicle), revealing substantial alignment in the degradation kinetics trends. Moreover, the achieved outcomes show the remarkable capability to identify salt crystallisation phenomenon type (efflorescence or subflorescence). [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
11. Three-Dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation.
- Author
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Zhang, Xianxia, Wang, Tangchen, Cheng, Chong, and Wang, Shaopu
- Subjects
DISTRIBUTED parameter systems ,STOCHASTIC approximation ,MACHINE learning ,THREE-dimensional modeling ,FUZZY numbers - Abstract
Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPSs). Due to the spatiotemporal coupling characteristics, the modeling of such systems is quite complex. The paper presents a new approach for three-dimensional fuzzy modeling using Simultaneous Perturbation Stochastic Approximation (SPSA) for nonlinear DPSs. The Affinity Propagation clustering approach is utilized to determine the optimal number of fuzzy rules and construct a collection of preceding components for three-dimensional fuzzy models. Fourier space base functions are used in the resulting components of three-dimensional fuzzy models, and their parameters are learned by the SPSA algorithm. The proposed three-dimensional fuzzy modeling technique was utilized on a conventional DPS within the semiconductor manufacturing industry, with the simulation experiments confirming its efficacy. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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12. New hybrid model for nonlinear systems via Takagi-Sugeno fuzzy approach.
- Author
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Mabrouk, Anouar Ben, Alanazi, Abdulaziz, Bassfar, Zaid, and Alanazi, Dalal
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FUZZY control systems ,NONLINEAR systems ,LYAPUNOV stability ,STABILITY theory ,RESEARCH personnel - Abstract
Mathematical models, especially complex nonlinear systems, are always difficult to analyze and synthesize, and researchers need effective and suitable control methods to address these issues. In the present work, we proposed a hybrid method that combines the well-known Takagi-Sugeno fuzzy model with wavelet decomposition to investigate nonlinear systems characterized by the presence of mixed nonlinearities. Here, one nonlinearity is super-linear and convex, and other is sub-linear, concave, and singular at zero, which leads to difficulties in the analysis, as is known in PDE theory. Linear and polynomial fuzzy models were combined with wavelets to ensure an improvement in both methods for investigating such problems. The results showed a high performance compared with existing methods via error estimates and Lyapunov theory of stability. The model was applied to a prototype nonlinear Schrodinger dynamical system. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
13. IoT-based flood disaster early detection system using hybrid fuzzy logic and neural networks.
- Author
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Kamali, Muhammad Adib and Palefi Ma’ady, Mochamad Nizar
- Subjects
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FUZZY neural networks , *FLOOD warning systems , *FLOODS , *FUZZY systems - Abstract
A flood stands as one of the most common natural occurrences, often resulting in substantial financial losses to property and possessions, as well as affecting human lives adversely. Implementing measures to prevent such floods becomes crucial, offering inhabitants ample time to evacuate vulnerable areas before flood events occur. In addressing the flood issue, numerous scholars have put forth various solutions, such as the development of fuzzy system models and the establishment of suitable infrastructure. However, when applying a fuzzy system, it often results in a loss of interpretability of the fuzzy rules. To address this issue effectively, we propose to reframe the optimization problem by incorporating stage costs alongside the terminal cost. Results show the proposed model called hybrid fuzzy logic and neural networks (NNs) can mitigate the loss of interpretability. Results also show that the proposed method was employed in a flood early detection system aligned with integrating into Twitter social media. The proposed concepts are validated through case studies, showcasing their effectiveness in tasks such as XOR-classification problems. [ABSTRACT FROM AUTHOR]
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- 2024
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14. МҰНАЙДЫ БАСТАПҚЫ ӨҢДЕУ ҚОНДЫРҒЫСЫНДА ТҰРАҚТЫ БЕНЗИН ӨНДІРУ ПРОЦЕСІН АЙҚЫНСЫЗДЫҚТА МОДЕЛЬДЕРІ НЕГІЗІНДЕ ОҢТАЙЛАНДЫРУ ТӘСІЛІ
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Оразбаев, Б. Б., Салыбек, Л. Т., Курмангазиева, Л. Т., Терехов, В. И., Утенова, Б. Е., Махатова, В. Е., and Өтебаева, А. С.
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PETROLEUM products , *PETROLEUM refining , *VEGETABLE oils , *MANUFACTURING processes , *PARETO principle , *GASOLINE - Abstract
This article examines the problems of optimizing the production process of stable gasoline based on models of the object, which is the target product of a primary oil refining installation, and proposes approaches to their effective solution. Currently, solving the problem of optimizing the main processes at a primary oil processing plant in the oil refining industry is one of the most pressing scientific and production problems, as it ensures the efficiency of further deep processing of the resulting petroleum products. In this regard, this study formulates a mathematical formulation of the problem of optimizing the production process of stable gasoline - the target product of the primary oil refining installation of the Atyrau Oil Refinery, characterized by uncertainty, and proposes a heuristic approach for its effective solution in a fuzzy environment. As a result of the research, mathematical models of complex objects characterized by ambiguity of some parameters, such as the stabilization column of a primary oil treatment plant, were developed, and on their basis a heuristic approach was developed that effectively optimizes the operation of the object in conditions of uncertainty. Models that determine the volumes of gasoline and gas from the stabilization column depending on the input operating parameters of the column are determined on the basis of experimental statistical data and the systematic application of the approach of sequential sequential connection of regressors and the least squares method. Fuzzy models that evaluate vaguely described quality indicators of stable gasoline are synthesized on the basis of expert assessment methods, fuzzy sets and modified methods of sequential inclusion of regressors, least squares. Based on the obtained models of the stabilization column, a heuristic algorithm has been developed for the effective optimization of the production process of stable gasoline under conditions of fuzzy conditions, based on a modification and combination of the principles of Pareto optimality and the ideal point for working in a fuzzy environment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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15. Finite-Time Fault-Tolerant Control of Nonlinear Spacecrafts with Randomized Actuator Fault: Fuzzy Model Approach.
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Xue, Wenlong, Jin, Zhenghong, and Tian, Yufeng
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FAULT-tolerant control systems , *MARKOV processes , *ACTUATORS , *NONLINEAR systems , *SPACE vehicles - Abstract
The primary objective of this paper is to address the challenge of designing finite-time fault-tolerant control mechanisms for nonlinear flexible spacecraft systems, which are particularly vulnerable to randomized actuator faults. Diverging from traditional methodologies, our research harnesses the capabilities of the Takagi–Sugeno (T–S) fuzzy framework. A unique feature of our model is the representation of actuator failures as stochastic signals following a Markov process, thereby offering a robust solution for addressing timeliness concerns. In this paper, we introduce a generalized reciprocally convex inequality that includes adjustable parameters, broadening the scope of previous results by accommodating them as special cases. Through the amalgamation of this enhanced inequality and flexible independent parameters, we propose an innovative controller design strategy. This approach establishes a stability standard that guarantees mean-square H ∞ performance. In order to validate the efficacy of the suggested strategy, we present a numerical illustration involving a nonlinear spacecraft system, showcasing the practical advantages and feasibility of our proposed technique. [ABSTRACT FROM AUTHOR]
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- 2024
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16. Artificial Intelligence-Based System for Retinal Disease Diagnosis.
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Orlova, Ekaterina V.
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DECISION support systems , *ARTIFICIAL intelligence , *RETINAL diseases , *EYE diseases , *DIAGNOSIS - Abstract
The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological methods can significantly improve and speed up the analysis of results and diagnostics. We propose an approach to designing an artificial intelligent diagnosis system (AI diagnosis system) which includes an electrophysiological complex to collect objective information and an intelligent decision support system to justify the diagnosis. The task of diagnosing retinal diseases based on a set of heterogeneous data is considered as a multi-class classification on unbalanced data. The decision support system includes two classifiers—one classifier is based on a fuzzy model and a fuzzy rule base (RB-classifier) and one uses the stochastic gradient boosting algorithm (SGB-classifier). The efficiency of algorithms in a multi-class classification on unbalanced data is assessed based on two indicators—MAUC (multi-class area under curve) and MMCC (multi-class Matthews correlation coefficient). Combining two algorithms in a decision support system provides more accurate and reliable pathology identification. The accuracy of diagnostics using the proposed AI diagnosis system is 5–8% higher than the accuracy of a system using only diagnostics based on electrophysical indicators. The AI diagnosis system differs from other systems of this class in that it is based on the processing of objective electrophysiological data and socio-demographic data about patients, as well as subjective information from the anamnesis, which ensures increased efficiency of medical decision-making. The system is tested using actual data about retinal diseases from the Russian Institute of Eye Diseases and its high efficiency is proven. Simulation experiments conducted in various scenario conditions with different combinations of factors ensured the identification of the main determinants (markers) for each diagnosis of retinal pathology. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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17. Fuzzy Model for Estimating the Worsening of Pathologies Due to Delays in Treatment.
- Author
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BROTONS-MARTÍNEZ, JOSÉ M., SANSALVADOR-SELLÉS, MANUEL E., and GONZÁLEZ-CARBONELL, JOSE F.
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TREATMENT delay (Medicine) ,CAUSES of death ,PATHOLOGY ,TIME delay estimation ,MATRICES (Mathematics) - Abstract
Based on accessible data such as the death registry, this work develops a methodology to provide an estimate of the number of patients and the level of aggravation of their pathologies due to delays in treatment. Firstly, for a given pathology, the deaths will be classified by the most common causes of death. The equivalent number of deceased patients can be obtained by adding this information through the Majority Ordered Weighted Average (MA-OWA). This aggregation will allow obtaining matrix C that indicates the incidence of delay in medical healthcare for each cause of death. Next, matrix L has been obtained, showing the nominal level for each type of patient whose pathology has been aggravated due to a delay in medical attention in each period. From matrices L and C, it is possible to obtain the matrix R that shows the fuzzy relationship between them. The worsening patients in a future period can be obtained from matrix L (obtained from matrix C of that future period and the previously calculated matrix R). Finally, an example illustrates the proposed theoretical model. [ABSTRACT FROM AUTHOR]
- Published
- 2024
18. A fuzzy model for studying kinetic decay phenomena in Genna Maria Nuraghe: Material properties, environmental data, accelerated ageing, and model calculations
- Author
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Marta Cappai, Ulrico Sanna, and Giorgio Pia
- Subjects
Accelerated ageing ,Archaeological site ,Environmental data ,Fuzzy model ,Decay kinetic ,Monitoring ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
In this study, a fuzzy model has been proposed for the control of the degradation process in Cultural Heritage. Specifically, the focus has been on the Nuragic building, Genna Maria, in Villanovaforru, Sardinia. Environmental data and material properties were considered to formalize inferences between different variables of the model. The results highlight the possibility of significant decay processes, such as salt crystallization and freeze-thaw cycles, estimated for all months of the year. A comparison between model elaborations and experimental data (material characterization, environmental data, accelerated ageing) demonstrates the reliability of the proposed procedure.
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- 2024
- Full Text
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19. Forecasting the Development of Information Security Events in the Context of Information Warfare
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Utenkova, Maria, Maksimova, Elena, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Lapina, Maria, editor, Raza, Zahid, editor, Tchernykh, Andrei, editor, Sajid, Mohammad, editor, Zolotarev, Vyacheslav, editor, and Babenko, Mikhail, editor
- Published
- 2024
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20. Emerging AI Technologies in Wastewater Treatment
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Singhal, Anshi, Pooja, Hooda, Sunita, Saya, Laishram, and Gulati, Shikha, editor
- Published
- 2024
- Full Text
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21. Z-Information-Based Designing a Sustainable Tourism Travel Trip
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Baysal, Ahmet Bahadir, Masmaliyev, Tahar, Mammadli, Omar, Nuriyev, Mahammad A., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Kahraman, Cengiz, editor, Cevik Onar, Sezi, editor, Cebi, Selcuk, editor, Oztaysi, Basar, editor, Tolga, A. Cagrı, editor, and Ucal Sari, Irem, editor
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- 2024
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22. Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY
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Guerreros, Diego Ricardo Cajachagua, Quijano, Sario Angel Chamorro, Meza, Felipe Nestor Gutarra, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, and Li, Shuliang, editor
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- 2024
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23. Risk Assessment at Unsignalized Intersections Based on Human-Road-Environment-Vehicle System Applying Fuzzy Logic
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Medvediev, Ievgen, Muzylyov, Dmitriy, Ivanov, Vitalii, Montewka, Jakub, Trojanowska, Justyna, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Pavlenko, Ivan, editor, Rauch, Erwin, editor, and Piteľ, Ján, editor
- Published
- 2024
- Full Text
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24. Fuzzy Optimization Model of Teaching Evaluation of Oral English Classroom in Colleges and Universities
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Ling, Mingyi, Tsihrintzis, George A., Series Editor, Virvou, Maria, Series Editor, Jain, Lakhmi C., Series Editor, Paas, Fred, editor, Patnaik, Srikanta, editor, and Wang, Taosheng, editor
- Published
- 2024
- Full Text
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25. Evaluation of Drinking Quality of Groundwater Using Fuzzy Logic and Deterministic Method
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Sedigheh Shakour, Manouchehr Chitsazan, and Yahya Mirzaee
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deterministic method ,fuzzy model ,groundwater ,schoeller ,Environmental sciences ,GE1-350 ,Water supply for domestic and industrial purposes ,TD201-500 - Abstract
Groundwater is the main source of drinking water in the northern Dezful-Andimeshk plain, Iran which has become saline in some cases. To check the drinking quality of groundwater, in October 2019, 16 samples were taken from different parts of the plain. The samples were analyzed for the concentration of major cations, anions, and nitrates.Two methods were used to evaluate water quality: the Schoeller deterministic method and the Fuzzy logic. The Schoeller method categorized water quality from good to bad and determined that 56.81, 20.83, 18.77, and 3.57% of the area had good, acceptable, inappropriate, and bad water quality, respectively. On the other hand, the Fuzzy method showed that 21.60% of the area had desirable groundwater with a confidence level of 70-81, 75.23% had acceptable water quality with a confidence level of 32-70, and 3.69% had non-acceptable quality with a confidence level of 20-22%. The Fuzzy method was found to be better in evaluating water quality as it provided a more comprehensive, accurate, and efficient assessment by covering uncertainties better.
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- 2024
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- View/download PDF
26. SCFS-securing flying ad hoc network using cluster-based trusted fuzzy scheme.
- Author
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Gupta, Shikha and Sharma, Neetu
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DENIAL of service attacks ,TRUST ,SOFTWARE failures ,AD hoc computer networks ,DYNAMICAL systems ,COMPUTER network security - Abstract
Flying Ad hoc Networks have emerged as a promising technology for number of real-time applications. However, the flexible and unstructured characteristics of these networks make them vulnerable to security threats posed by malicious nodes, such as denial of service attacks, node impersonation, and information breaches. Another major issue is the consideration of those nodes being unable to prove their trustworthiness due to factors like hardware or software failure, or by link interruptions, during the processing of detection of false nodes in the network. The existing mechanisms encompassing encryption, authentication, and intrusion detection highlight limitations to secure real-time applications and services due to the high speed of flying nodes and the absence of fixed network structures. To overcome these constraints, this research paper incorporates a novel framework for evaluating and improving the security of network by introducing an innovative cluster-based approach. Moreover, it presents a fuzzy model that dynamically estimates the trust levels of both individual nodes and clusters, by assigning weight to the parameters to address vulnerabilities. Additionally, a trust reconfiguration mechanism is further proposed to address the issue of nodes unable to substantiate their trust by providing them with additional chances based on the collective trust from previous evaluations. Further, the paper incorporates a dynamic reputation system to proficiently identify and separate malicious and selfish nodes from the network. Simulation results indicate a significant improvement in performance metrics, with a considerable reduction in delay and drop ratio by 41.46% and 36.37%, respectively, while the sufficient rise of 54.71% and 46.05% in throughput and coverage, respectively, comparing with the considered state-of-art. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
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27. NON-ANALYTICAL DESIGN OF THE PI CONTROLLER OPTIMAL PARAMETERS FOR A CONTINUOUS LINE.
- Author
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PERDUKOVA, DANIELA and FEDOR, PAVOL
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NONLINEAR dynamical systems ,MIMO systems ,NONLINEAR systems - Abstract
The multiple motor drives are complex and coupled MIMO nonlinear systems. Due to the complexity of their mathematical models the development of effective control systems is quite complicated task. This paper presents the design of optimal control based on the quadratic optimality criterion for the central section of the continuous production line using soft computer methods when fuzzy model of the controlled system has been used. In this case, the proposed method demonstrates non-analytical design of the optimal parameters of PI controller with emphasis on minimal knowledge on the controlled system. The realized experimental measurements on a continuous line laboratory model confirmed the effectiveness and the good dynamic properties of the optimal continuous line controller and also its applicability to others MIMO nonlinear dynamic systems. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
28. A Fuzzy-Based Analysis of Air Particle Pollution Data: An Index IMC for Magnetic Biomonitoring.
- Author
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Chaparro, Mauro A. E., Chaparro, Marcos A. E., and Molinari, Daniela A.
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PARTICULATE matter , *AIR pollution , *AIR analysis , *AIR pollutants , *REMANENCE , *BIOLOGICAL monitoring - Abstract
Airborne magnetic particles may be harmful because of their composition, morphology, and association with potentially toxic elements that may be observed through relationships between magnetic parameters and pollution indices, such as the Tomlinson pollution load index (PLI). We present a fuzzy-based analysis of magnetic biomonitoring data from four Latin American cities, which allows us to construct a magnetic index of contamination (IMC). This IMC uses four magnetic parameters, i.e., magnetic susceptibility χ, saturation isothermal remanent magnetization SIRM, coercivity of remanence Hcr, and SIRM/χ, and proposes summarizing the information to assess an area based exclusively on magnetic parameters more easily. The fuzzy inference system membership functions are built from the standardization of the data to become independent of the values. The proposed IMC is calculated using the baseline values for each case study, similar to the PLI. The highest IMC values were obtained in sites close to industrial areas, and in contrast, the lowest ones were observed in residential areas far from avenues or highways. The linear regression model between modeled IMC and PLI data yielded robust correlations of R2 > 0.85. The IMC is proposed as a complementary tool for air particle pollution and is a cost-effective magnetic approach for monitoring areas. [ABSTRACT FROM AUTHOR]
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- 2024
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- View/download PDF
29. Robust and quantized repetitive tracking control for fractional‐order fuzzy large‐scale systems.
- Author
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Tharanidharan, V., Saravanakumar, T., and Anthoni, S. Marshal
- Subjects
- *
FUZZY systems , *ITERATIVE learning control , *TIME delay systems , *STABILITY theory , *LYAPUNOV stability , *DESIGN techniques , *ARTIFICIAL satellite tracking - Abstract
Summary: In this article, the decentralized repetitive tracking controller design for fractional‐order large‐scale Takagi–Sugeno fuzzy system with time delays is developed. We mainly focus on the design of a decentralized repetitive tracking controller based on the Lyapunov stability theory, by which the addressed large‐scale system asymptotically stabilized with H∞$$ {H}_{\infty } $$ performance index. Further, the repetitive control with quantized signal is developed to ensure the good tracking performance with the presence of interconnected model and external disturbances. Specifically, a logarithmic quantizer is used to quantify the control signal which can reduce the data transmission rate in the network. Finally, a numerical example is presented to verify the effectiveness of the proposed controller design technique. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
30. Elective surgery scheduling considering transfer risk in hierarchical diagnosis and treatment system.
- Author
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Zongli Dai and Jian-Jun Wang
- Subjects
FAILURE mode & effects analysis ,MIXED integer linear programming ,ELECTIVE surgery ,COLUMN generation (Algorithms) ,HOSPITAL beds - Abstract
With the aggravation of the shortage of staffing hospital beds, elective surgeries have to be postponed or even cancelled, which directly affects hospital income and patient health. Therefore, we propose a fuzzy scheduling model based on a patient transfer strategy in the hierarchical diagnosis and treatment system to ensure timely surgery. We propose a risk estimation method based on health failure mode and effect analysis to reduce the transfer risk and represent the surgery duration and the length of stay as fuzzy numbers to deal with the uncertainty. Given that solving the fuzzy model is challenging, we propose an equivalent formulation to transform the fuzzy model into a two-stage mixed integer linear programming (TMIP) model, which can reduce the loss of decision-making information. Finally, the column and constraint generation algorithm is used to solve the TMIP model that is suited for the structure of the main problem and subproblem. The experiment shows that the patient transfer strategy can effectively relieve the hospital bed shortage, and its potential can be further released if the transfer risk can be properly assessed. The proposed method for solving the fuzzy model can reduce the information loss comparing traditional methods. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
31. مکان یابی بهینه پایگاههای چند منظوره مدیریت بحران با استفاده از سیستم اطلاعات جغرافیایی (مطالعه موردی مناطق ۴ و ۱۰ شهرداری تبریز).
- Author
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مینا محسن زاده, علیرضا محمدی, and حسین نظم فر
- Abstract
Thus, in recent years, the construction of sites to support crisis management has been high on the agenda of crisis management of Tabriz. One of the things to consider before constructing these databases is study and select a suitable location for the establishment of this type of use.In this study, a multi-location site of crisis management has been studied in Regions 4 and 10 of Tabriz Municipality. In the first instance, was paid to identify and analyze factors influencing site's Site selection. Raster maps were obtained after collection and preparation of the layers, and then weighting parameters was performed using the AHP in software Expertchoice. Next, the information layer, integrated with each other, based on fuzzy models, and finally combining the results of this stage, the options as desired location, were introduced, among their southern part of the four, was identified as the preferred option. Due to the geographic information system, in solving complex urban issues, and facilitate spatial analysis, has been applied, from ability of this system to prepare, integrate and analyze of layers. as a result of this extraction, bakhsh, south of the 4 region, has the address of a garden, which indicates the appointment of a suitable monthly residential property, such as sabz, amuzshi, warzahi, and ... appropriate domestic policies and conditions this is priority to buy for the stability of this water.i am going to the place of my neighbourhood, and iam connected to it, park Hai Amir Kabir. [ABSTRACT FROM AUTHOR]
- Published
- 2024
32. SCFS-securing flying ad hoc network using cluster-based trusted fuzzy scheme
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Shikha Gupta and Neetu Sharma
- Subjects
Cluster ,Observers ,Fuzzy model ,Malicious nodes ,FANET ,Omnetpp ,Electronic computers. Computer science ,QA75.5-76.95 ,Information technology ,T58.5-58.64 - Abstract
Abstract Flying Ad hoc Networks have emerged as a promising technology for number of real-time applications. However, the flexible and unstructured characteristics of these networks make them vulnerable to security threats posed by malicious nodes, such as denial of service attacks, node impersonation, and information breaches. Another major issue is the consideration of those nodes being unable to prove their trustworthiness due to factors like hardware or software failure, or by link interruptions, during the processing of detection of false nodes in the network. The existing mechanisms encompassing encryption, authentication, and intrusion detection highlight limitations to secure real-time applications and services due to the high speed of flying nodes and the absence of fixed network structures. To overcome these constraints, this research paper incorporates a novel framework for evaluating and improving the security of network by introducing an innovative cluster-based approach. Moreover, it presents a fuzzy model that dynamically estimates the trust levels of both individual nodes and clusters, by assigning weight to the parameters to address vulnerabilities. Additionally, a trust reconfiguration mechanism is further proposed to address the issue of nodes unable to substantiate their trust by providing them with additional chances based on the collective trust from previous evaluations. Further, the paper incorporates a dynamic reputation system to proficiently identify and separate malicious and selfish nodes from the network. Simulation results indicate a significant improvement in performance metrics, with a considerable reduction in delay and drop ratio by 41.46% and 36.37%, respectively, while the sufficient rise of 54.71% and 46.05% in throughput and coverage, respectively, comparing with the considered state-of-art.
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- 2024
- Full Text
- View/download PDF
33. Fractional Caputo Operator and Takagi–Sugeno Fuzzy Modeling to Diabetes Analysis
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Ez-zaiym Mustapha, El Ouissari Abdellatif, El Moutaouakil Karim, and Aberqi Ahmed
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fractional derivative ,Takagi–Sugeno fractional ,diabetes ,artificial intelligence ,fuzzy model ,Mathematics ,QA1-939 - Abstract
Diabetes is becoming more and more dangerous, and the effects continue to grow due to the population’s ignorance of the seriousness of this phenomenon. The studies that have been carried out have not been able to follow the phenomenon more precisely, which has led to the use of the fractional derivative tool, which has a very great capability to study real problems and phenomena but is somewhat limited on nonlinear models. In this work, we will develop a new fractional derivative model of a diabetic population, the Takagi–Sugeno fractional fuzzy model, which will enable us to study the phenomenon with these nonlinear terms in order to obtain greater precision in the results. We will study the existence and uniqueness of the solution using the Lipschizian theorem and then turn to the new fuzzy model, which leads us to four dynamical systems. The interpretation results show the quality of fuzzy membership in tracking the malleable phenomena of nonlinear terms existing in the system.
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- 2024
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34. Solving the Problem of Fuzzy Partition-Distribution with Determination of the Location of Subset Centers
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Anatoly Bulat, Elena Kiseleva, Sergiy Yakovlev, Olga Prytomanova, and Danylo Lebediev
- Subjects
operation research ,location-allocation problem ,optimal partitioning ,fuzzy model ,infinite-dimensional mathematical programming ,non-differentiable optimization ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
A large number of real-world problems from various fields of human activity can be reduced to optimal partitioning-allocation problems with the purpose of minimizing the partitioning quality criterion. A typical representative of such problem is an infinite-dimensional transportation problem and more generalized problems—infinite-dimensional problems of production centers placement along with the partitioning of the area of continuously distributed consumers with the purpose of minimizing transportation and production costs. The relevant problems are characterized by some kind of uncertainty level of a not-probabilistic nature. A method is proposed to solve an optimal fuzzy partitioning-allocation problem with the subsets centers placement for sets of n-dimensional Euclidean space. The method is based on the synthesis of the methods of fuzzy theory and optimal partitioning-allocation theory, which is a new science field in infinite-dimensional mathematical programming with Boolean variables. A theorem was proved that determines the form of the optimal solution of the corresponding optimal fuzzy partitioning-allocation problem with the subsets centers placement for sets of n-dimensional Euclidean space. An algorithm for solving fuzzy partitioning-allocation problems is proposed, which is based on the proved theorem and on a variant of Shor’s r-algorithm—a non-differential optimization method. The application of the proposed method is demonstrated on model tasks, where the coefficient of mistrust is integrated to interpret the obtained result—the minimum value of the membership function, which allows each point of the set partition to be assigned to a specific fuzzy subset.
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- 2024
- Full Text
- View/download PDF
35. Event‐triggered security control for fuzzy‐model‐based cyber‐physical systems under Denial‐of‐Service attacks and actuator faults.
- Author
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Tan, Cheng, Gao, Chengzhen, Ding, Tongtong, Peng, Jinzhu, and Zhang, Fangfang
- Subjects
- *
CYBER physical systems , *DENIAL of service attacks , *ACTUATORS , *MATRIX inequalities , *LINEAR matrix inequalities , *FUZZY neural networks , *RESOURCE allocation , *HOPFIELD networks - Abstract
This article addresses the issue of event‐triggered security control for nonlinear cyber‐physical systems, characterized by Denial‐of‐Service (DoS) attacks, time‐varying delays, and actuator faults. These complexities are captured using the Takagi–Sugeno fuzzy model. Significantly, this study focuses on DoS attacks targeting the controller‐to‐actuator channel, and subsequently introduces a model for actuator faults that considers the prolonged utilization or degradation of component parts. To optimize communication resource allocation, a model‐independent event‐triggered mechanism is proposed. Utilizing the Lyapunov–Krasovskii function approach, the objective of achieving stochastic stability is transformed into a linear matrix inequalities problem, thus deriving a set of sufficient conditions. The efficiency and validity of the proposed algorithms is demonstrated through simulation results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
36. پهنه بندی خطر سیل در مناطق خشک با استفاده از مدل ترکیبی AHP در شهرستان دشتی جنوب ایران.
- Author
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سعید زارعی and سعیده کشاورز
- Abstract
Floods have been considered the most common natural disaster worldwide in recent years. Flood hazard potential mapping is required for the management and mitigation of flood. Climatic change and the occupation of rivers and drainage have led to floods in arid areas. The objective of this study is to assess and zoning flood risk using the AHP-FUZZY hybrid approach model in the Dashti region of Bushehr Province. In this study, precipitation, elevation, slope, drainage density, land use, geology and soil parameters were used. These parameters have been constructed and classified in the ARC GIS Software; which were weighed according to the AHP method in AHP SOLVER software and the layers were fuzzy using the fuzzy model. Finally, by combining the AHP-FUZZY method, the flood risk assessment and zoning map were obtained.6.5% of the area is in the very high-risk range, and 27.9% is in the high-risk range. Analysis of the final map shows that Khormuj, Sana and Shonbeh are at greater risk of flooding. The combination of the AHP-FUZZY method in previous research has confirmed that this method has great capacity in flood risk assessment and zoning. Therefore, knowing the flood potential of the basin can be effective in formulating crisis management plans when faced with floods. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
37. A risk warning method for steady-state power quality based on VMD-LSTM and fuzzy model
- Author
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Yu Shen, Wei Hu, Mingqi Dong, Fan Yang, Zhichun Yang, and Hechong Chen
- Subjects
Power quality ,Risk warning ,Variational mode decomposition ,Long short-term memory ,Fuzzy model ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
The risk warning for steady-state power quality in the power grid is essential for its prevention and management. However, current risk warning methods fall short in predicting the power quality trend while accounting for potential risks. Consequently, this study introduces a novel steady-state power quality risk warning method utilizing VMD-LSTM and a fuzzy model. Firstly, a power quality index prediction method based on variational mode decomposition (VMD) and long short-term memory (LSTM) is proposed. This approach significantly enhances prediction accuracy. Secondly, a power quality risk warning method incorporating kernel density estimation (KDE) and a fuzzy model is proposed, which systematically addresses the uncertainty associated with power quality risks. To validate the effectiveness and practicality of the proposed method, experiments are conducted using field monitoring data from a residential load in southern China. The results affirm the reliability and applicability of the proposed method. The simulation results show that the median error of prediction of power quality indexes by the proposed method is 5.03 % during the evaluated time period, and the prediction accuracy is mostly maintained above 90 %.
- Published
- 2024
- Full Text
- View/download PDF
38. On the Local Coordination of Fuzzy Valuations
- Author
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G. E. Yakhyaeva
- Subjects
fuzzy model ,theory of fuzzy models ,fuzzy measure ,coordinated valuation ,locally coordinated valuation ,Mathematics ,QA1-939 - Abstract
The paper is devoted to the model-theoretic formalization of the semantic model of the object domain. The article discusses the concept of a fuzzy model, which is a model where the truth function exhibits properties of a fuzzy measure. We demonstrate that a fuzzy model is a generalization of the concept of fuzzification of a precedent (semantic) model to include a countable number of precedents. In practice, it is common to have partial expert knowledge about the set of events in the object domain, making it difficult to immediately describe the fuzzy model. Additionally, since expert valuations are subjective, they may be incorrect and inconsistent with any fuzzy model. In the article, we introduce the concepts of coordinated and locally coordinated valuation of a set of sentences, and provide proofs for interval theorems and an analogue of the compactness theorem.
- Published
- 2023
- Full Text
- View/download PDF
39. Three-Dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation
- Author
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Xianxia Zhang, Tangchen Wang, Chong Cheng, and Shaopu Wang
- Subjects
distributed parameter system ,fuzzy model ,simultaneous perturbation stochastic approximation ,fuzzy modeling ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPSs). Due to the spatiotemporal coupling characteristics, the modeling of such systems is quite complex. The paper presents a new approach for three-dimensional fuzzy modeling using Simultaneous Perturbation Stochastic Approximation (SPSA) for nonlinear DPSs. The Affinity Propagation clustering approach is utilized to determine the optimal number of fuzzy rules and construct a collection of preceding components for three-dimensional fuzzy models. Fourier space base functions are used in the resulting components of three-dimensional fuzzy models, and their parameters are learned by the SPSA algorithm. The proposed three-dimensional fuzzy modeling technique was utilized on a conventional DPS within the semiconductor manufacturing industry, with the simulation experiments confirming its efficacy.
- Published
- 2024
- Full Text
- View/download PDF
40. Finite-Time Fault-Tolerant Control of Nonlinear Spacecrafts with Randomized Actuator Fault: Fuzzy Model Approach
- Author
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Wenlong Xue, Zhenghong Jin, and Yufeng Tian
- Subjects
nonlinear spacecraft ,fuzzy model ,fault-tolerant control ,randomized actuator fault ,Mathematics ,QA1-939 - Abstract
The primary objective of this paper is to address the challenge of designing finite-time fault-tolerant control mechanisms for nonlinear flexible spacecraft systems, which are particularly vulnerable to randomized actuator faults. Diverging from traditional methodologies, our research harnesses the capabilities of the Takagi–Sugeno (T–S) fuzzy framework. A unique feature of our model is the representation of actuator failures as stochastic signals following a Markov process, thereby offering a robust solution for addressing timeliness concerns. In this paper, we introduce a generalized reciprocally convex inequality that includes adjustable parameters, broadening the scope of previous results by accommodating them as special cases. Through the amalgamation of this enhanced inequality and flexible independent parameters, we propose an innovative controller design strategy. This approach establishes a stability standard that guarantees mean-square H∞ performance. In order to validate the efficacy of the suggested strategy, we present a numerical illustration involving a nonlinear spacecraft system, showcasing the practical advantages and feasibility of our proposed technique.
- Published
- 2024
- Full Text
- View/download PDF
41. Artificial Intelligence-Based System for Retinal Disease Diagnosis
- Author
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Ekaterina V. Orlova
- Subjects
artificial intelligence ,decision support system ,fuzzy model ,rule-based algorithms ,stochastic gradient boosting algorithm ,retinal disease diagnosis ,Industrial engineering. Management engineering ,T55.4-60.8 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
The growth in the number of people suffering from eye diseases determines the relevance of research in the field of diagnosing retinal pathologies. Artificial intelligence models and algorithms based on measurements obtained via electrophysiological methods can significantly improve and speed up the analysis of results and diagnostics. We propose an approach to designing an artificial intelligent diagnosis system (AI diagnosis system) which includes an electrophysiological complex to collect objective information and an intelligent decision support system to justify the diagnosis. The task of diagnosing retinal diseases based on a set of heterogeneous data is considered as a multi-class classification on unbalanced data. The decision support system includes two classifiers—one classifier is based on a fuzzy model and a fuzzy rule base (RB-classifier) and one uses the stochastic gradient boosting algorithm (SGB-classifier). The efficiency of algorithms in a multi-class classification on unbalanced data is assessed based on two indicators—MAUC (multi-class area under curve) and MMCC (multi-class Matthews correlation coefficient). Combining two algorithms in a decision support system provides more accurate and reliable pathology identification. The accuracy of diagnostics using the proposed AI diagnosis system is 5–8% higher than the accuracy of a system using only diagnostics based on electrophysical indicators. The AI diagnosis system differs from other systems of this class in that it is based on the processing of objective electrophysiological data and socio-demographic data about patients, as well as subjective information from the anamnesis, which ensures increased efficiency of medical decision-making. The system is tested using actual data about retinal diseases from the Russian Institute of Eye Diseases and its high efficiency is proven. Simulation experiments conducted in various scenario conditions with different combinations of factors ensured the identification of the main determinants (markers) for each diagnosis of retinal pathology.
- Published
- 2024
- Full Text
- View/download PDF
42. New Fuzzy Logic-Based Hybrid Overlay (NFLHyO) in P2P Live Streaming
- Author
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Tehariya, Sanjay Kumar, Ahmed, Mushtaq, Bansal, Jagdish Chand, Series Editor, Deep, Kusum, Series Editor, Nagar, Atulya K., Series Editor, Kumar, Sandeep, editor, Hiranwal, Saroj, editor, Purohit, S.D., editor, and Prasad, Mukesh, editor
- Published
- 2023
- Full Text
- View/download PDF
43. Fuzzy Model of Defence of the Defensive Line by a Group of Dynamic Objects
- Author
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Bayramov, Azad, Pashayev, Adalat, Sabziev, Elkhan, Kacprzyk, Janusz, Series Editor, Shahbazova, Shahnaz N., editor, Abbasov, Ali M., editor, Kreinovich, Vladik, editor, and Batyrshin, Ildar Z., editor
- Published
- 2023
- Full Text
- View/download PDF
44. Fuzzy Method of Creating of Thematic Catalogs of Information Resources of the Internet for Search Systems
- Author
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Gasimov, Vagif, Xhafa, Fatos, Series Editor, Hemanth, D. Jude, editor, Yigit, Tuncay, editor, Kose, Utku, editor, and Guvenc, Ugur, editor
- Published
- 2023
- Full Text
- View/download PDF
45. Assessing the Impact of Innovations on the Volume of Production of the Final Product in a Fuzzy Information Environment
- Author
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Akhundov, V. J., Rustamov, İ. S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Aliev, R. A., editor, Kacprzyk, J., editor, Pedrycz, W., editor, Jamshidi, Mo., editor, Babanli, M. B., editor, and Sadikoglu, F., editor
- Published
- 2023
- Full Text
- View/download PDF
46. Predicting Bitcoin Prices Using ANFIS and Haar Model
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Jaber, Jamil J., Alkhawaldeh, Rami S., Alkhawaldeh, Samar M., Masa’deh, Ra’ed, Alshurideh, Muhammad Turki, Kacprzyk, Janusz, Series Editor, Alshurideh, Muhammad, editor, Al Kurdi, Barween Hikmat, editor, Masa’deh, Ra’ed, editor, Alzoubi, Haitham M., editor, and Salloum, Said, editor
- Published
- 2023
- Full Text
- View/download PDF
47. A Novel Approach for Non-linear Deep Fuzzy Rule-Based Model and Its Applications in Biomedical Analyses
- Author
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Davoodi, Raheleh, Moradi, Mohammad Hassan, Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Hatzilygeroudis, Ioannis K., editor, and Tsihrintzis, George A., editor
- Published
- 2023
- Full Text
- View/download PDF
48. Design and Development of Micro-grid Networks for Demand Management System Using Fuzzy Logic
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Senthil, L., Sharma, Ashok Kumar, Sharma, Piyush, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Noor, Arti, editor, Saroha, Kriti, editor, Pricop, Emil, editor, Sen, Abhijit, editor, and Trivedi, Gaurav, editor
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- 2023
- Full Text
- View/download PDF
49. The Learning of Fuzzy Models Based on the Fuzzy Bayesian Approach
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Borisov, Vadim, Luferova, Elena, Luferov, Victor, Sukhanov, Andrey, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Kovalev, Sergey, editor, Sukhanov, Andrey, editor, Akperov, Imran, editor, and Ozdemir, Sebnem, editor
- Published
- 2023
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- View/download PDF
50. Formation of Subsets of Co-expressed Gene Expression Profiles Based on Joint Use of Fuzzy Inference System, Statistical Criteria and Shannon Entropy
- Author
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Liakh, Igor, Babichev, Sergii, Durnyak, Bohdan, Gado, Iryna, Xhafa, Fatos, Series Editor, Babichev, Sergii, editor, and Lytvynenko, Volodymyr, editor
- Published
- 2023
- Full Text
- View/download PDF
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