检索结果-南通市图书馆

Chinese Journal of Electronics 2016年第1期25卷 13-19页

作者： ding weiping GUAN Zhijin SHI Quan School of Computer Science and Technology Nantong University State Key Laboratory for Novel Software Technology Nanjing University

In order to further analyze the dynamical behavior of co-evolutionary populations in minimum attribute reduction, an Enhanced attribute co-evolutionary game reduction(EACGR) algorithm by integrating selfadaptive multi-level Nash equilibrium is proposed in this paper. First, a self-adaptive multi-level Nash game model with cross co-evolution is designed to provide the better solution for the dynamical symmetric co-evolution of multi-populations. Second, the profit matrix of elitist energy is constructed to explore the payoff mechanism of coevolutionary selection. And then a novel Nash equilibrium strategy is adopted to perform attribute co-evolutionary game reduction so that the admissible balance of attribute reduction can be well achieved. Experimental results indicate that EACGR has the higher performance of minimum attribute reduction, and the application into 3D brain MRI segmentation with promising results indicates its stronger robustness and practicability.

关键词： Cross co-evolutionary game Profit matrix of elitist energy Multi-level Nash equilibrium Minimum attribute reduction

Cooperative extended rough attribute reduction algorithm based on improved PSO

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2012年第1期23卷 160-166页

作者： weiping ding Jiandong Wang Zhijin Guan College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 E R. China School of Computer Science and Technology Nantong University Nantong 226019 E R. China

Particle swarm optimization （PSO） is a new heuristic algorithm which has been applied to many optimization problems successfully. Attribute reduction is a key studying point of the rough set theory, and it has been proven that computing minimal reduc- tion of decision tables is a non-derterministic polynomial （NP）-hard problem. A new cooperative extended attribute reduction algorithm named Co-PSAR based on improved PSO is proposed, in which the cooperative evolutionary strategy with suitable fitness func- tions is involved to learn a good hypothesis for accelerating the optimization of searching minimal attribute reduction. Experiments on Benchmark functions and University of California, Irvine （UCI） data sets, compared with other algorithms, verify the superiority of the Co-PSAR algorithm in terms of the convergence speed, efficiency and accuracy for the attribute reduction.

关键词： rough set extended attribute reduction particle swarm optimization (PSO) cooperative evolutionary strategy fitness function.

A Survey on Type-3 Fuzzy Logic Systems and Their Control Applications

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1744-1756页

作者： Oscar Castillo Fevrier Valdez Patricia Melin weiping ding Tijuana Institute of Technology/Tecnologico Nacional de Mexico Division of Graduate StudiesCalzada Tecnologico S/NTijuana 22414Mexico School of Information Science and Technology Nantong UniversityJiangsu 226019China

In this paper,we offer a review of type-3 fuzzy logic systems and their applications in *** main objective of this work is to observe and analyze in detail the applications in the control area using type-3 fuzzy logic *** this case,we review their most important applications in control and other related topics with type-3 fuzzy *** algorithms have been receiving increasing attention in control and for this reason a review in this area is *** paper reviews the main applications that make use of Intelligent Computing ***,type-3 fuzzy logic *** aim of this research is to be able to appreciate,in detail,the applications in control systems and to point out the scientific trends in the use of Intelligent Computing *** is done with the construction and visualization of bibliometric networks,developed with VosViewer Software,which it is a free Java-based program,mainly intended to be used for analyzing and visualizing bibliometric *** this tool,we can create maps of publications,authors,or journals based on a co-citation network or construct maps of keywords,countries based on a co-occurrence networks,research groups,etc.

关键词： Applications control systems optimization review type-3 fuzzy logic.

A Quantum Tanimoto Coefficient Fidelity for Entanglement Measurement

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 439-450页

作者： Yangyang Zhao Fuyuan Xiao Masayoshi Aritsugi weiping ding the School of Big Data and Software Engineering Chongqing UniversityChongqing 401331China IEEE the Faculty of Advanced Science and Technology Kumamoto UniversityKumamoto 860-8555Japan the School of Information and Technology Nantong UniversityNantong 223019China

Fidelity plays an important role in quantum information processing,which provides a basic scale for comparing two quantum *** present,one of the most commonly used fidelities is Uhlmann-Jozsa(U-J)***,U-J fidelity needs to calculate the square root of the matrix,which is not trivial in the case of large or infinite density ***,U-J fidelity is a measure of overlap,which has limitations in some cases and cannot reflect the similarity between quantum states ***,a novel quantum fidelity measure called quantum Tanimoto coefficient(QTC)fidelity is proposed in this *** other existing fidelities,QTC fidelity not only considers the overlap between quantum states,but also takes into account the separation between quantum states for the first time,which leads to a better performance of ***,we discuss the properties of the proposed QTC *** fidelity is compared with some existing fidelities through specific examples,which reflects the effectiveness and advantages of QTC *** addition,based on the QTC fidelity,three discrimination coefficients d_(1)^(QTC),d_(2)^(QTC),and d_^(3)^(QTC)are defined to measure the difference between quantum *** is proved that the discrimination coefficient d_(3)^(QTC)is a true ***,we apply the proposed QTC fidelity-based discrimination coefficients to measure the entanglement of quantum states to show their practicability.

关键词： Distance measure entanglement measurement fidelity measure quantum Tanimoto coefficient(QTC) similarity measure uncertainty

Three-Way Behavioral Decision Making With Hesitant Fuzzy Information Systems:Survey and Challenges

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 330-350页

作者： Jianming Zhan Jiajia Wang weiping ding Yiyu Yao the School of Mathematics and Statistics Hubei Minzu UniversityEnshi 445000China Xidian University Xi’an 710126China IEEE the School of Computer Science and Technology Nantong UniversityNantong 226019China the Department of Computer Science University of ReginaRegina S4S 0A2Canada

Three-way decision(T-WD)theory is about thinking,problem solving,and computing in *** decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used *** hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership *** by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and ***,we provide a brief historical account of the three topics and present basic ***,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing ***,we point out key challenges and future research directions.

关键词： Hesitant fuzzy information system(HFIS) prospect theory regret theory three-way decision(T-WD)

Enhanced minimum attribute reduction based on quantum-inspired shuffled frog leaping algorithm

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2013年第3期24卷 426-434页

作者： weiping ding Jiandong Wang Zhijin Guan Quan Shi College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics School of Computer Science and Technology Nantong University State Key Laboratory for Novel Software Technology Nanjing University

Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction.

关键词： minimum attribute reduction quantum-inspired shuf- fled frog leaping algorithm multi-state quantum bit quantum rotation gate and quantum mutation elitist frog.

A Layered Co-evolution Based Rough Feature Selection Using Adaptive Neighborhood Radius Hierarchy and Its Application in 3D-MRI

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2017年第6期26卷 1168-1176页

作者： ding weiping GUAN Zhijin WANG Jiehua TIAN Di School of Computer Science and Technology Nantong University State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology

As the conventional feature selection algorithms are prone to the poor running efficiency in largescale datasets with interacting features, this paper aims at proposing a novel rough feature selection algorithm whose innovation centers on the layered co-evolutionary strategy with neighborhood radius hierarchy. This hierarchy can adapt the rough feature scales among different layers as well as produce the reasonable decompositions through exploiting any correlation and interdependency among feature subsets. Both neighborhood interaction within layer and neighborhood cascade between layers are adopted to implement the interactive optimization of neighborhood radius matrix, so that both the optimal rough feature selection subsets and their global optimal set are obtained efficiently. Our experimental results substantiate the proposed algorithm can achieve better effectiveness, accuracy and applicability than some traditional feature selection algorithms.

关键词： Layered co-evolution Rough feature se lection Adaptive neighborhood radius hierarchy Longitudinal cortical surface labeling

Ensemble feature selection integrating elitist roles and quantum game model

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2015年第3期26卷 584-594页

作者： weiping ding Jiandong Wang Zhijin Guan Quan Shi College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics School of Computer Science and Technology Nantong University Provincial Key Laboratory for Computer Information Processing Technology Soochow University

To accelerate the selection process of feature subsets in the rough set theory （RST）, an ensemble elitist roles based quantum game （EERQG） algorithm is proposed for feature selec- tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles＇ performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec- tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Finally, the en- semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which will greatly improve the fea- sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.

关键词： ensemble quantum game utility matrix of trust mar-gin dynamics equilibrium strategy multilevel elitist role feature selection and classification.

A Cascaded Co-evolutionary Model for Attribute Reduction and Classification Based on Coordinating Architecture with Bidirectional Elitist Optimization

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2017年第1期26卷 13-21页

作者： ding weiping WANG Jiandong LI Yuehua CHENG Xueyun School of Computer Science and Technology Nantong University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Provincial Key Laboratory for Computer Information Processing Technology Soochow University College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics

A cascaded co-evolutionary model for Attribute reduction and classification based on Coordinating architecture with bidirectional elitist optimization(ARC-CABEO) is proposed for the more practical applications. The regrouping and merging coordinating strategy of ordinary-elitist-role-based population is introduced to represent a more holistic cooperative co-evolutionary framework of different populations for attribute reduction. The master-slave-elitist-based subpopulations are constructed to coordinate the behaviors of different elitists, and meanwhile the elitist optimization vector with the strongest balancing between exploration and exploitation is selected out to expedite the bidirectional attribute co-evolutionary reduction process. In addition, two coupled coordinating architectures and the elitist optimization vector are tightly cascaded to perform the co-evolutionary classification of reduction subsets. Hence the preferring classification optimization goal can be achieved better. Some experimental results verify that the proposed ARC-CABEO model has the better feasibility and more superior classification accuracy on different UCI datasets, compared with representative algorithms.

关键词： Attribute reduction for classification Bidirectional elitist optimization Coordinating architecture Cascaded co-evolutionary model

Cyberbullying and Cyberviolence Detection:A Triangular User-Activity-Content View

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1384-1405页

作者： Shuwen Wang Xingquan Zhu weiping ding Amir Alipour Yengejeh Department of Electrical Engineering and Computer Science Florida Atlantic UniversityBoca RatonFL 33431 USA School of Information Science and Technology Nantong UniversityNantong 226019China

Recent years have witnessed the increasing popularity of mobile and networking devices,as well as social networking sites,where users engage in a variety of activities in the cyberspace on a daily and real-time *** such systems provide tremendous convenience and enjoyment for users,malicious usages,such as bullying,cruelty,extremism,and toxicity behaviors,also grow noticeably,and impose significant threats to individuals and *** this paper,we review computational approaches for cyberbullying and cyberviolence detection,in order to understand two major factors:1)What are the defining features of online bullying users,and 2)How to detect cyberbullying and *** achieve the goal,we propose a user-activities-content(UAC)triangular view,which defines that users in the cyberspace are centered around the UAC triangle to carry out activities and generate ***,we categorize cyberbully features into three main categories:1)User centered features,2)Content centered features,and 3)Activity centered *** that,we review methods for cyberbully detection,by taking supervised,unsupervised,transfer learning,and deep learning,etc.,into *** UAC centered view provides a coherent and complete summary about features and characteristics of online users(their activities),approaches to detect bullying users(and malicious content),and helps defend cyberspace from bullying and toxicity.

关键词： Classification clustering cyberbullying natural language processing social network