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6th International Conference on Software Engineering and Computer Science, CSECS 2023

作者： Deng, Wenbin Zheng, Wenjie Yan, Li Pei, Zheng School of science Xihua University Sichuan Chengdu610039 China Center for Radio Administration & Technology Development College of Science Xihua University Sichuan Chengdu610039 China

ISBN: (纸本)9798350306378

This article introduces interval-valued Z-number with interval and linguistic value. It is a reliable tool to explain the vagueness or unclear boundary of linguistic in multiple attribute group decision making. This article uses linguistic scale functions to compute interval-valued with linguistic. Firstly, the operations of IVZN are defined, therefore two types of aggregation operators are proposed to aggregate information. The ranking result are calculated through the score function and accuracy function. Finally, an example of airbus type selection is used to further verify the practicability of the method. © 2023 IEEE.

关键词： Linguistics

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An Improved TODIM Method With Z-number and Its Application in Ranking 22

An Improved TODIM Method With Z-number and Its Application i...

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6th International Conference on Computer Science and Application Engineering, CSAE 2022

作者： Deng, Wenbin Wu, Meiqi Pei, Zheng School of Science Xihua University Sichuan Chengdu610039 China Center for Radio Administration & Technology Development College of Science Xihua University Sichuan Chengdu610039 China

ISBN: (纸本)9781450396004

To address the Multi-criteria Decision Making (MCDM) with Z-number information, this paper first proposes a Jaccard distance with Z-number information based on Jaccard distance, then explores and proves the property of this distance, and combines this distance into the TODIM method with Z-number for decision making. Finally, an example is used to verify the feasibility of the method, and the flexibility and superiority of the method are highlighted through parameter and comparative analysis. © 2022 Association for Computing Machinery.

关键词： Decision making

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Interval-Valued Z-Number Aggregation Operators and Its Application in Airbus Type Selection Problem

Interval-Valued Z-Number Aggregation Operators and Its Appli...

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Software Engineering and Computer Science (CSECS), International Conference on

作者： Wenbin Deng Wenjie Zheng Li Yan Zheng Pei School of science Xihua University Chengdu Sichuan China Center for Radio Administration & Technology Development College of Science Xihua University Chengdu Sichuan China

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Application of Adaptive Fuzzy Spiking Neural P Systems in Fault Diagnosis of Power Systems

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Chinese Journal of Electronics 2025年第1期23卷 87-92页

作者： Min Tu Jun Wang Hong Peng Peng Shi School of Electrical and Information Engineering Xihua University Chengdu China Center for Radio Administration and Technology Development Xihua University Chengdu China Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd UK School of Engineering and Science Victoria University Melbourne Vic Australia

Adaptive fuzzy spiking neural P systems (AFSN P systems) are a novel kind of computing models with parallel computing and learning ability. Based on our existing works, AFSN P systems are applied to deal with the fault diagnosis problems of power systems and the uncertainty of action messages about protective relays and breakers, and a new fault diagnosis model of power systems is proposed with simple reasoning process and fast speed with parallel processing capabilities. The effectiveness of the fault diagnosis model is verified by some examples of fault diagnosis. Furthermore, the learning ability of AFSN P systems can be applied to adjust the weights in the fault diagnosis model automatically.

关键词： Fault diagnosis Adaptation models Technological innovation Adaptive systems Uncertainty Scientific computing Computational modeling Parallel processing Transformers Research and development

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Multi-scale Two-Way Deblurring Network for Non-uniform Single Image Deblurring 14th

Multi-scale Two-Way Deblurring Network for Non-uniform Singl...

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14th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2021

作者： Cheng, Zhongzhe Luo, Bing Xu, Li Li, Siwei Xiao, Kunshu Pei, Zheng The Center for Radio Administration Technology Development School of Computer and Software Engineering Xihua University Chengdu610039 China The School of Science Xihua University Chengdu610039 China Xihua College of Xihua University Chengdu610039 China

ISBN: (纸本)9783030898137

We propose a new and effective image deblurring network based on deep learning. The motivation of this work is based on traditional algorithms and deep learning which take an easy-to-difficult approach to image deblurring. In traditional algorithms, a rough blur kernel is obtained first, and then a precise blur kernel is gradually refined. In deep learning, the pyramid structure is adopted to restore clear images from easy to difficult. We hope to recover the clear image by two-way approximation. One network recovers the roughly clear image from the blurred image, and the other network recovers part of the structural information from the blank image, and finally the two networks are added together to obtain the clear image. Experiments show that since we decomposed the original deblurring task into two different tasks, the network performance has been effectively improved. Compared with other latest networks, our network can get clearer images. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Image enhancement

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A New Multiple Attribute Group Decision-making Approach to the Selection of Hotels for a Travel Company 20

A New Multiple Attribute Group Decision-making Approach to t...

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4th International Conference on Computer Science and Application Engineering, CSAE 2020

作者： Li, Qingzhao Rong, Yuan Pei, Zheng School of Science Xihua University Chengdu Sichuan China Center for Radio Administration and Technology Development Xihua University Chengdu Sichuan China

ISBN: (纸本)9781450377720

This paper proposes a new multi-attribute group decisionmaking (MAGDM) approach to conduct decision analysis with q-rung orthopair fuzzy (q-ROF) information, whose weights of attributes are completely unknown, based on Frank operations and improved Additive Ratio Assessment (ARAS). Firstly, we put forward the new operational laws of q-rung orthopair fuzzy number (q-ROFN) based on Frank operations. Then, we further give q-rung orthopair fuzzy Frank prioritized weighted (q-ROFFPWA) and q-rung orthopair fuzzy Frank prioritized weighted geometric (q-ROFFPWG) operator to aggregate fuzzy information effectively and study some properties of them. Furthermore, we propound an improved ARAS method to address MAGDM problem, where the weights of attributes determined through a newly defined generalized entropy. At last, we test the practicality of the proposed method by applying it to the selection of hotels for a travel company, and highlight the flexibility and superiority of this method by parameter analysis and comparative analysis. © 2020 ACM.

关键词： Decision making

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A Novel Q-rung Orthopair Fuzzy Multi-attribute Group Decision-making Approach Based on Schweizer-sklar Operations and Improved COPRAS Method 20

A Novel Q-rung Orthopair Fuzzy Multi-attribute Group Decisio...

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4th International Conference on Computer Science and Application Engineering, CSAE 2020

作者： Rong, Yuan Li, Qingzhao Pei, Zheng School of Science Xihua University Chengdu Sichuan China Center for Radio Administration and Technology Development Xihua University Chengdu Sichuan China

ISBN: (纸本)9781450377720

This essay propounds an innovative multi-attribute group decision-making (MAGDM) methodology to address the issues which the weight information of attributes is complete unknown under q-rung orthopair fuzzy set (q-ROFS) context based upon Schweizer-Sklar (SS) operations and complex proportional assessment (COPRAS) method. To begin with, the q-rung orthopair fuzzy Schweizer-Sklar weighted averaging (q-ROFSSWA) and its geometric form i.e., q-ROFSSWG operator are presented to integrate the assessment information of experts. Besides, several valuable properties of these operators are proved. Furthermore, a MAGDM methodology through combining the developed operators and COPRAS method is proffered to cope with q-ROFMAGDM problems where the weight is objective ascertained by the Spearman method. Ultimately, the validation and applicability of the developed approach are verified through a numerical example and the superiority and flexibility are separately highlighted through the comparative investigation and parameter analysis. © 2020 ACM.

关键词： Decision making

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New Distance and Entropy for Linguistic Intuitionistic Fuzzy Set and their Application to Linguistic Decision Making 14

New Distance and Entropy for Linguistic Intuitionistic Fuzzy...

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14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019

作者： Lu, Xiaofang Zhang, Qiaoqiao Rong, Yuan Pei, Zheng Chen, Zichun Xi Hua University School of Sience Chengdu China Xi Hua University Center for Radio Administration Technology Development Chengdu China

ISBN: (纸本)9781728123486

In order to handle the multi-attribute group decision making(MAGDM) problems with linguistic intuitionistic fuzzy (LF) information, a modified TOPSIS method is proposed with LF entropy and LF distance measure. Firstly, the linguistic metric function(LMF) is defined as a tool to quantity LF information, and the new LF entropy is further introduced to derive the attribute weights. Secondly, based on the classical cosine similarity, the new distance measure between linguistic intuitionistic fuzzy sets(LIFSs) is developed, which is called the LF induced ordered weighted distance(LIFIOWD) measure. Subsequently, a modified TOPSIS method based on LF entropy and the LFIOWD measure is presented for linguistic decision making(LDM). Finally, the example of a car company choosing a wheel manufacturer is used to demonstrate this approach. © 2019 IEEE.

关键词： Linguistics

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User Experience Evaluation of Shared Bikes with Intuitionistic Fuzzy Information 14

User Experience Evaluation of Shared Bikes with Intuitionist...

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14th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2019

作者： Zhang, Qiaoqiao Rong, Yuan Lu, Xiaofang Pei, Zheng Xi Hua University School of Science Chengdu China Xi Hua University Center for Radio Administration Technology Development Chengdu China

ISBN: (纸本)9781728123486

User experience could be considered as a comprehensive experience that includes the user's attitude towards a product or company service. The target of this paper is to provide a framework to evaluate user experience of shared bikes. Firstly, the evaluation index framework of shared bikes is established from the aspects of payment, safety problems, distribution pattern, Internet services. Then, we obtained the satisfaction scores of users on various indexes of shared bikes by means of questionnaire. We apply this quantitative result to the ranking of shared bike brands and find the difference between actual user experience and ideal user experience, so as to improve of the insufficient performance of shared bikes. The ranking of shared bike brands can be deemed to a multiple criteria decision making (MCDM) problem. The ratings of shared bikes on criteria can be expressed in the form of intuitionistic fuzzy sets(IFSs), the reason for using this form is that determining them is commonly depended on the decision maker's intuition in some situations. Finally, we analyze the data from the survey to obtain user experience evaluation of shared bikes. © 2019 IEEE.

关键词： Surveys

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A quick algorithm on generating concept lattice for attribute-incremental streaming data 21

A quick algorithm on generating concept lattice for attribut...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Yang, Yixuan Hao, Fei Pang, Beibei Qin, Keyun Pei, Zheng Li, Bo School of Computer Science Shaanxi Normal University Xi'an China School of Mathematics Southwest Jiaotong University Chengdu China Center for Radio Administration and Technology Development Xihua University Chengdu China School of Information Science and Technology Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781728120584

The explosive information growth facilitates the generation of increasingly massive streaming data. As a traditional soft computing approach for data analysis, Formal Concept Analysis (FCA) has the severe problem of low efficiency and long time for coping with massive streaming data. Therefore, devising an optimized efficiency algorithm of FCA for attribute-incremental streaming data is becoming a very urgent and challenging issue. In this paper, a quick algorithm on generating concept lattice for attribute-incremental streaming data is presented. Specifically, the correctness of the proposed algorithm is mathematically proved, and several real-world data sets are utilized in our experiments in order to compare with the existing two FCA algorithms. Experimental results demonstrate that the proposed algorithm significantly improves the efficiency for generating concept lattice of attribute-incremental streaming data. Particularly, the running time could be reduced by approximately 44% for Jazz dataset. © 2019 IEEE.

关键词： Efficiency

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