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Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office 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.)

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office 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.)

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of 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.)

Timely and effective treatment of negative online reviews can improve the reputation of enterprises and maintain the trust of consumers. However, facing a large number of negative online reviews, it is difficult for enterprises to respond effectively in a short time. According to the characteristics that online reviews are short texts, negative online reviews based on sentence similarity are used for case-based reasoning. Aiming at the problem of sentence similarity calculation of negative online reviews, this paper extracted the evaluation object words and evaluation words as keywords, and considered the modifiers of evaluation words and sentence semantic dependency association pairs. In addition to the three features of keywords, modifiers and semantic dependency analysis association pairs, this paper proposed a sentence similarity calculation method which integrated five features of common words, keywords, modifiers, semantics and semantic dependency analysis association equivalence to retrieve similar negative reviews sentences. The experimental results show that the sentence similarity calculation method based on multi features is better than the common sentence similarity calculation methods, and its accuracy rate is 83. 3 %. It can effectively retrieve the case sentence set and automatically recommend the reply scheme. [ABSTRACT FROM AUTHOR]

In the parallel simulation deducing based on real-time situation, the uncertainty of battlefield requires the ability of multi-branch simulation. In the process of multi-branch extension, the generation of related branches is realized by the traction of decision points. The traditional decision point selection depends on expert system, which is difficult to meet the requirement of parallel simulation on the efficiency of decision point generation. This paper analyzes the difference between off-line multi-branch inference and real-time multi-branch inference, and proposes a parallel simulation-oriented decision point generation strategy. Based on case-based reasoning, decision points are quickly determined and generated to realize real-time multi-branch inference, which reduces the generation of some invalid branches and guarantees the credibility and effectiveness of multi-branch generation under parallel simulation. [ABSTRACT FROM AUTHOR]

Building defects information is normally stored in discrete and unstructured way, for this reason it has become an important field in related research to build up the case-based reasoning framework of building defects for enhancing the level of building maintenance management. In this paper, according to the multi-attribute building defect model, a defect collection sample corresponding to the international classification standards has been designed to capture core contents of defect information, and defect domain ontology is developed based on the defect categories. Then, a multi-attribute classified case-databased of building defect is constructed using case-based distance approach. By calculating the distance between the typical case with defect level and the case group center point, an optimization model of the multiattribute weights is proposed to simplify the complex comparison process of multi attributes in decision making related to building defects. In this paper, a defect case-based reasoning framework with classified case-databased is designed to verify the effectiveness of the calculation method of case similarity which is performed with a preprocessing of classified information of building defects. The analytical result shows that the proposed method has a good performance in solving multi-attribute classification of building defects. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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.)

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security 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.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office 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.)

Aiming at the problem of channel and power allocation in centralized cognitive networks, this paper proposed a case-based reasoning and improved heuristically accelerated Q-learning algorithm. In order to improve the convergence speed of the Q-learning algorithm, it matched the current allocation problem with the stored historical case, and selected the Q value of the most similar case, which was normalized as the initial value of the heuristically accelerated Q-learning algorithm. In order to improve the performance of the heuristically accelerated Q-learning, it introduced a guidance function based on information intensity to change the action strategy by emphasizing the importance of the action; it considered energy efficiency in the design of the reward function. The simulation results show that the proposed algorithm can significantly improve the system energy efficiency and convergence speed, which has carried the channel and power allocation. [ABSTRACT FROM AUTHOR]

As the product manufacturing time could not be obtained quickly and accurately under the mass customization environment, this paper explored how to calculate the manufacturing time of customized products. Firstly, according to the modular theory, this paper divided the manufacturing time into the characteristic time module ( physical time module, logical time module) and the sub characteristic time module (operating time module, custom time module). Then, it used the CBR technology to determine the quota of operating time and analyzed mechanism which custom factors influenced the manufacturing time, and built separately the quota model of custom time module and mathematical model of product manufacturing time. At last, the practical application of the transformer (G) in a company verified the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Based on the geometric feature of plastic product, aiming at two primary parts of ejection design that are ejector type selection and ejector location, this paper used rule-based reasoning to obtain fitted ejector as well as case-based reasoning to decide ejector location and ejector quantity. And this paper also discussed the critical method of cases frame representation and cases similar metric based on fuzzy similarity ratio. An example was provided at the end of the paper. Rule based reasoning and case based reasoning are two different technologies which use experience to resolve new problems and this paper brings them to the ejection design to overcome disadvantage of designers lacking experience. [ABSTRACT FROM AUTHOR]

Molten steel temperature is a parameter in converter end-point control. Accurate prediction of molten steel temperature is crucial for converter end-point control. However, most of the previous end-point prediction models are static models, which can only predict the molten steel temperature at the end-point of converter blowing and cannot realize dynamic prediction, affording a limited role for these models. To solve this challenge, a data-driven prediction model of molten steel temperature in the second blowing stage in a converter is proposed. First, the model retrieves the similar cases in the historical case base through the process parameters in the main blowing stage of the new case, such as carbon content and temperature of TSC measurement, based on the case-based reasoning (CBR) algorithm. Second, the process parameters in the second blowing stage of the similar cases, such as oxygen flow, lance position, and argon flow, are used to train the relationship between the process parameters and the molten steel temperature based on the long short-term memory (LSTM) algorithm. Third, the trained LSTM model is used to dynamically calculate the molten steel temperature in the second blowing stage of the new case. Finally, the actual production data is divided into five sets for cross-validation, and the model prediction accuracy changes are tested when the number of reuse cases ranges from 1 to 10, and the number of neurons is 5, 10, 15, and 20. The results show that, on the one hand, the prediction accuracy of the model first increases and then decreases with an increasing number of cases, and when the number of reused cases is 4, the prediction accuracy of the model is the highest, indicating that the number of cases is increased when training the model. Improving the prediction accuracy of the model is beneficial; however, the reference value of the case decreases with the similarity of the case, reducing the prediction accuracy of the model. Conversely, when the number of neurons is 10, the prediction accuracy of the model reaches it’s the highest value. The hit rate of the prediction error in the range of [−5 ℃, 5 ℃], [−10 ℃, 10 ℃], and [−15 ℃, 15 ℃] reached 40.33%, 68.92%, and 88.33%, respectively. This paper also establishes the traditional quadratic model and cubic model as well as further proves the effectiveness of the model by comparing the three indicators of these models, namely, the RMSE, MSE, and hit rate.

Copyright of Chung Cheng Educational Studies is the property of Chung Cheng University, College of Education 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.)

Emergencies beyond the experience, but they also depend on experience. Application of casebased reasoning is effective way of drawing lessons from historical case; it is useful to clarify the evolution of emergency response scenario. Facing the complex disaster situation with multi-stage, multi-objective and multi-subject, single domain case base system is difficult to meet the requirement. It needs to build domain-general integrated case base. In this paper, the taxonomy method and case similarity metric are employed to design case pedigree. The longitudinal dimension, horizontal dimension of case pedigree and their relationship are illustrated with scenario evolution by considering event chain and scenario similarity metric respectively. Based on the proposed frame theory, an example is given n the city of Shenzhen to build related case pedigree. [ABSTRACT FROM AUTHOR]

Rule based reasoning and case based reasoning are two different techniques which use experience to resolve problems. It is benefit to the development of intelligence of die & mold manufacturing to apply these two techniques in tool selection. Based on the properties of cutting tool design, this paper introduced the criteria of dividing and ruling and divided the tool design into two different subtasks. Rule-based reasoning and case-based reasoning were used in two subtasks respectively. It also investigated the representation of case, similar measure of cases based on fuzzy degree of nearness and the weight of case features. At last, an example was given to illustrate the procedure of geometric parameters decision of cutting tool using case based reasoning. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office 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.)