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In order to solve the problem of multiple classification, based on the idea of explicit and implicit factor in factor space theory, the algorithm of sweeping class serial classification is proposed, the merging of categories is defined, and an explicit and implicit method of merging class sweep classification is proposed. The algorithm steps are given and analyzed by numerical examples. The pair wise combination is defined and the pairwise class sweep classification method with explicit and implicit factors is proposed, the algorithm steps are given and analyzed by numerical examples. During the execution of two algorithms, for the occurrence of decision categories can not be separated, the absolute value method of difference with explicit and implicit factors is proposed to solve the problem. Three examples in UCI dataset are compared with support vector machine, the results show that the proposed method of merging class sweep classification and the pairwise sweep classification method can realize factor explicit and implicit, and the accuracy of classification algorithm is better than that of the support vector machine. The conclusion of explicit and implicit study of factors in multi-classification learning expands the theoretical and applied research of factor space. [ABSTRACT FROM AUTHOR]

Factor space is a method for determining the relationship between internal and external factors affecting the construction process. Internal factors are the processes controlled by the developer or investor during the realization of a construction project. Internal factors include: planning, controlling, intensity, quality, cost and operational reliability. External factors are conditions that cannot be influenced by the developer or investor during the realization of a construction project. External factors include: natural conditions, permafrost degradation and infrastructure. Analyzing the factor space in the construction of pile foundations on permafrost provides construction companies with the opportunity to achieve the following objectives: 1. Identification of the main factors: factor space analysis allows to identify the main aspects that have the greatest influence on the technological process. 2. Interrelationships between factors: factor space analysis helps to explore the interrelationships between different factors and understand how they interact with each other. 3. Process Optimization: factor space analysis helps to identify opportunities for optimizing processes, materials and resources. This helps in improving the efficiency and quality of pile foundation construction, achieving better results. 4. Risk Management: factor space analysis helps to identify potential risks associated with various factors and develop strategies to mitigate or avoid them. This allows for better management of risks associated with unpredictable permafrost characteristics and other factors affecting the foundation construction process. Thus, factor space analysis in permafrost pile foundation construction is an important tool for developing optimal strategies and making informed decisions that contribute to successful project implementation.

Objective The factors affecting the stability of an open pit slope are complex and fuzzy. Hence, it is difficult to evaluate the stability through mathematical and mechanical analysis methods. Methods According to the actual engineering characteristics and in-situ investigation of an open pit, four first-class evaluation indexes including landform, geological structure, rock mass properties and occurrence environment and 17 second-class evaluation indexes were determined. The stability evaluation model of open pit slope based on factor space is established. Firstly, the analytical hierarchy process(AHP) and entropy weight method are used to calculate the subjective and objective weights, and the combined weights of the factors affecting the stability of the open pit slope are given. Then, the unascertained measure theory is used to construct the measure function, calculate the single factor measurement matrix to evaluate the slope stability, reduce the dimension of the factor space through factor synthesis, and generate the combined factor measure vector. Finally, the stability of the open pit slope is evaluated through the confidence recognition criteria. Taking the typical slope profile of the eastern slope of Qidashan open pit iron mine as an example, the factor space evaluation results are compared with the calculation results of the limit equilibrium method and the finite difference method, and the reliability of the slope evaluation method is verified. Results The results show that the evaluation results of factor space model are basically consistent with the results obtained from the field investigation, and are consistent with the calculation results of limit equilibrium method and finite difference method, which verifies the accuracy and scientificity of the established factor space evaluation model. Based on the comprehensive analysis of the factor space evaluation results and the calculation results of other methods, four slope profile protection and treatment suggestions are given. Conclusion The factor evaluation model simplifies the process of slope stability evaluation, improves the accuracy of the evaluation results of the model, and can provide a reference for the stability evaluation of an open pit slope with similar geological conditions.

The development of construction complexes in modern economic conditions is conditioned by the significant impact of negative environmental factors due to geopolitical and macroeconomic crisis phenomena. There is a need to develop approaches to strategic management of construction enterprises and their associations in order to improve sustainability and competitiveness in domestic and foreign markets. The specifics of the development of modern of the investment and construction complex (ICC) enterprises lies in the complexity of the approach to the creation of finished construction products, consisting in the complication of production and economic relations between enterprises, the increase in the number of participants in production processes in construction, the development of mechanisms of corporate associations of individual ICC entities. As an object of strategic management within the framework of the ICC, it is reasonable to consider construction groups as a key form of corporate intra-industry interaction of enterprises of various specializations, which allows to realize to the greatest extent the possibilities of implementing flexible organizational modelling mechanisms both at the level of the construction group and within the functioning of its individual participants. The solution of the tasks of strategic management of the construction group should be implemented when the conditions for maximizing the level of strategic development are met, while ensuring a sufficient level of general stability of the construction group. The key aspect of developing an approach to the formation and development of strategic management approaches is the definition of the factor space that affects the functioning of the managed system as a whole and, as a consequence, the level of its organizational and economic stability. The results of the study allowed the author to form the structure of the general stability of the construction group with an indication of the relationship of individual elements of stability and key factors-indicators of stability at each level of management of the company. The presented structural model of the general stability of the construction group contributes to the development of methodological tools in the implementation of a systematic approach to the strategic management of construction groups and enterprises operating in their composition.

The article focuses on mathematical modeling when using biopolymer reagents based on gums, produced by various manufactures through enzymatic methods. These manufactures include the domestic brand KK (Russia), Kem-X (USA), and Rodopol-23R (France). The use of these reagents in drilling muds imparts pseudoplastic properties, which are crucial for the successful drilling of multi-meter horizontal intervals and the effective penetration of productive formations in various fields across Russia, particularly in the Volga-Ural region. Equations of dynamic shear stress (DSS) and effective viscosity (EV) were obtained depending on the concentration of the studied gums (biopolymer reagents) and shear rate. These equations represent functions of two variables, visualized as surfaces in three-dimensional space. The two axes correspond to the independent variables (concentration and shear rates), while the third axis represents the value of the function (DSS, EV). Analysis of the obtained data and dependencies from experimental results revealed that an increase in shear rate leads to an increase in dynamic shear stress for water-based muds utilizing KK gum, while it decreases for muds using Kem-X and Rodopol-23R reagents. At the same time, the effective viscosity of muds using the KK reagent decreases with increasing shear rate, whereas muds with Kem-X and Rodopol-23R reagents display the opposite trend. Comparative analysis of the regression equations for the main parameters of drilling muds using these reagents made it possible to assess the effectiveness of various gums (biopolymer reagents), both domestic and foreign production. It has been shown that the domestic biopolymer reagent based on KK gum not only matches the performance of its foreign counterparts (Kem-X and Rodopol-23R), but also surpasses them in terms of exhibiting pseudoplastic properties in drilling mud compositions. [ABSTRACT FROM AUTHOR]

• Intelligent representation and reasoning of SFEP and fault concept extraction. • Factor code-pedigree are combined to represent the topology of SFEP. • Knowledge element expression describes the minimum unit of SFEP. • Extract the fault concept by the knowledge increasing expression. • Code the unit using factor code to establish the factor pedigree of the unit. The key to information fusion lies in the clarification and integration of the information domains comprising all information and using factor space is an effective way to achieve the above goals. We studied the intelligent representation and logical reasoning of the system fault evolution process (SFEP), determined the relationship between factor influence and fault state and proposed an SFEP intelligent decision method based on factor space theory. The focus and innovation of this study lies in the combination of factor code and factor pedigree with space fault network to represent the topology of SFEP to extract and analyse the fault concept and realise intelligent analysis and decision of the fault process. The results show that the minimum unit can be expressed as a factor code, and the factor pedigree can be formed by knowledge increase expression. The frequency and the probability of the four phases of the fault concept under the action of a single- factor and multiple factors, as well as the proportion of certainty and uncertainty, were obtained. This study provides the basic theory and intelligent decision method for the formation of the fault concept in the SFEP considering information fusion. [ABSTRACT FROM AUTHOR]

Human resource management plays an important role in modern enterprises. As a fundamental element of human resource management, the evaluation of human performance is receiving more and more attention. Great deal of attention in the literature was given for evaluation results, whereas the studies focused on provide performance feedback for future improvement are less. In this paper, a multifactor human performance evaluation approach based on the factor space theory is designed. The fuzzy sets is applied to construct the evaluation functions, and the fuzzy multifactor mapping is used to synthesize the evaluated values. Unlike other evaluation approaches, the proposed method can not only evaluate the performance of candidates based on criteria, but also provide some constructive criticism or suggestions for employees in professional and personal improvement. Finally, an example in employees' performance evaluation is presented to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, statistical learning methods are widely used. Among all artificial intelligence problems, obtaining excellent training models through massive data mining and huge computing power is currently a hot topic. Although such statistical learning methods have shown great potential in academic and industrial applications, the causal logic of machine learning still has poor interpretability. In the factor space theory proposed in 1982, Professor Peizhuang Wang first proposed causal reasoning to find the relationship between causation and effect and created factor space to illustrate causal relationships. Factors play a vital role in the factor space, which can be applied in various scenarios. The projection method provides a way of thinking and perspective for finding factors by projecting the vectors in the n-dimensional real vector space Rn into subspace, and this method has great value in knowledge representation and causal reasoning. [ABSTRACT FROM AUTHOR]

We demonstrate that characterizing the minimal dimension of the term structure of interest rates is more challenging than currently appreciated. The highly structured polynomial patterns of the factor loadings, which are widely reported and discussed in the literature, reflect local correlations of smooth curves across maturities. We derive analytical expressions for the loadings of cross-sectionally dependent processes that tend to favor a much lower dimension than the true dimension of the underlying factor space. Numerical examples illustrate the significant economic costs of erroneously committing to a parsimoniously parameterized factor space that is informed by standard metrics of goodness-of-fit. Our results apply to other assets with a finite maturity structure. [ABSTRACT FROM AUTHOR]

In order to expand the application field of causal analysis under the theory of factor space, based on the idea of induction of inverse logic under the theory of factor space, the probability distribution of the causal sentences is calculated using background distribution to describe the strength of the inference rules, reverse logic causal analysis algorithm is proposed and applied to bank credit analysis, and the bank credit card default prediction model based on the theory of factor space is proposed. This method takes credit card actual measured data as the background sample to extract the inference rules, and tests the predictive inference rules with the other sample data. The experimental results on UCI data sets show that the reverse causality analysis algorithm is accurate to predict the default result of credit card users and the method is feasible. [ABSTRACT FROM AUTHOR]

In order to reduce the complexity of the calculation of causal rule extraction using multiple targets causality analysis method, the definition of multiple targets factor condition reduction dimension mapping and drill in decision degree reduction dimension are given. Target factors are combined. Target factors are reducted according to drilling determination of selected target factors to judge results, and the target factor reduction algorithm is obtained. On the basis of the dimension reduction algorithm of the objective factors, the relevance between the objective factors is studied, the definition of the correlation index is given, and the dimension reduction algorithm of the multiple targets causal analysis is obtained by combining the multiple targets causal analysis method. The research results show that the dimension reduction algorithm of the multiple targets causal analysis is practical and effective. The research results bring some new space for the multiple targets optimization. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To understand the system function-structure under different background relations, two analysis methods are proposed based on space fault tree and factor space theory. They are the system function-structure minimal disjunctive formula and the system function-structure simplest formula. The former establishes the axiom system of system function-structure analysis based on factor logic, and proves that the system function-structure obtained by function-structure analysis method is a minimal disjunction formula. The latter gives a more detailed analysis steps based on the former idea, which is mainly used to determine the implicit relation between system function and component function. The background sets consisting of the 16 and 32 background relations are studied with these two methods. The results show that the complete background relations can obtain a certain system function-structure uniquely; the incomplete background relations can obtain a family of certain system function-structures. If the incomplete background relations are a subset of the complete background relations, then the incomplete background relations must has a linear relation between functions to complement the incomplete background relations. At the same time, the system function equivalent and replacement relation are obtained. It is also proved that the system function-structure obtained from several subsets of the background sets is the simplest and the condition required for the simplest structure of the background set is strict. At present, the above methods are mainly used for system reliability analysis in safety system engineering. [ABSTRACT FROM AUTHOR]

In the present paper we consider preserving orientation Morse-Smale diffeomorphisms on surfaces. Using the methods of factorization and linearizing neighbourhoods we prove that such diffeomorphisms have a finite number of orientable heteroclinic orbits. [ABSTRACT FROM AUTHOR]

Accurately assessing the health condition of the power transformer is critical to improving the operational reliability of power systems. Although great efforts to improve the accuracy of transformer fault diagnosis, accurate detection of multiple latent faults is still a difficult problem. Therefore, a multifactorial condition assessment method based on fuzzy sets and factor space is proposed. Different from the previous diagnosis methods that only provide a single‐valued result, the proposed method can display the influence degree of various variables on the condition assessment result, which indirectly indicates the cause and location of faults that occur in a transformer. In the proposed method, the type‐2 fuzzy set is used to describe the evaluation of various test values and the multifactorial condition assessment model based on factor space is applied to integrate the condition information. A modified analytic hierarchy process method is developed to estimate the relative importance of attributes. This method can distinctly indicate multiple probable latent faults of the transformer and help engineers quickly determine the cause and location of faults, which is helpful to improve the accuracy of diagnosis and the efficiency of transformer maintenance. The effectiveness of this method is verified with case studies. [ABSTRACT FROM AUTHOR]

In order to adapt to the randomness of large data, based on the background distribution in the factor space, the measurability of the factor space is studied, and the measurability and measurability factors space are obtained. Then the randomness is introduced into the factor space, and the factor random process, factor Markov process theory, nature, and application are given. The data reasoning of Markov process randomness and factor space is combined, and the randomness field of factor space theory is expanded. From another point of view, the reasons for background distribution, random process, and Markov process are explained. It provides a new prediction method for dealing with factors with no latency. [ABSTRACT FROM AUTHOR]

The system reliability is related to the factors which affect the system reliability in a multi-factor influencing environment. At the same time, the cumulative fault data increases rapidly as the system operates. These big data magnitude fault data also contains system reliability characteristics. Therefore, it is urgent to solve the problem of system reliability analysis which is suitable for big data and multi factors. The research adopts the method of space fault tree (SFT) and factor space (FS), which are proposed by the author to solve these problems. SFT can solve the system reliability analysis under the influence of many factors. FS has the ability of large data processing and logic analysis. Fault probability is used to represent reliability, FS is introduced into SFT. The logical relationship between reliability and influencing factors is studied, and we also put forward the corresponding analysis method. On the basis of the existing research, the SFT theory is improved, which can be used to infer the causal relationship, reduce factor dimension and compress fault data. This research is the intersection of safety system science and information science intelligent technology. It can provide the basic theory and application method for the reliability analysis of various industrial and mining enterprises, military and other fields. [ABSTRACT FROM AUTHOR]

At present, the oil and gas SCADA system is facing severe information security threats, and the information security assessment for the existing SCADA system is an important response measure. In order to solve the problem that the standard of information security assessment of industrial control system are not perfect and the evaluation objects are fuzzy, this study put forward a novel method of oil and gas SCADA security assessment based on causality analysis. Firstly, defense security assessment technology route with pre-defense,post-defense was introduced and the evaluation indexes were mapped to the pre-defense and post-defense factors, and the pre-defense and post-defense scoring tables for oil and gas SCADA system information security were developed, the evaluation factors were formed as causality diagram table; then the factor space theory was used to evaluate and model the information security of oil and gas SCADA system, and the model was formally described. Finally causality analysis evaluation method of fuzzy Mamdani reasoning was adopted to evaluate factors neurons in the proposed model. The results show that the average accuracy of the causality analysis and the decision tree algorithm is 92.06 and 91.45% respectively. The causality analysis method based on factor space has a good effect on SCADA information security assessment. The conclusions of this study can not only be applied to oil and gas SCADA security risk assessment, but also provide a reference for other industry security assessment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Heilongjiang University of Science & Technology is the property of Journal of Heilongjiang University of Science & Technology Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to make the space fault tree theory have the ability to analyze the discrete reliability data,this paper proposed a simplest formula analysis method of the system function structure based on the factor space theory. The method mainly used to understand the causal relationship between the system function and the component function. It given the steps of the simplest formula analysis method of the system function structure and related definitions. It composed the system of 32 fault states,which could be used to analyze the relationship between system function and component function. At the same time,it random chosen 23 fault states to form an background relation subset,and obtained the function relation. By comparing the difference between the two kinds of function relations,according to the Boolean algebra,it got the implicit function relation between components: the function of component Z3 was the same as that of Z1 or Z2 or Z1+ Z2. Thus,it obtained the component equivalence and substitution relation of system reliability. At the same time,the sum of the minimal extraction paradigms of the two background relation subsets was not equal to that of original background relation,and given the condition of equality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we for the first time propose an framework of intelligent mathematics, which consists of factor space, information diffusion, and internet of intelligences. This paper demonstrates how to use intelligent mathematics to describe earthquake risk perception. The concept of earthquake risk is described in the factor space, and the knowl- edge of earthquake risk is formed in association learning based on information diffusion. Different knowledge sys- tems precipitate different acquired consciousnesses. The security instinct affects the perception of risk. For a region, the risk consciousnesses of the stakeholders could be integrated with the internet of intelligences to form a consen- sus of the earthquake risk perception.

Based on summarising and analyzing the research status of policy research and the technology of concept description, this paper proposes an effective mining method of recessive lineage relationship between policies. This method introduces the theory of factor space and gives a method for decomposing concept factor. We introduce the recessive gene as a new "synonym" and calculate the fitting degree of policy texts to reveal the recessive lineage relationship, which cannot be reflected through the direct calculation of similarity. Finally, we use the articles of law as the set of policy texts to carry out a large number of experiments. The comparison and analysis of the experimental results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]