Fuzzy Sets and Operations Research
- Conference proceedings
- © 2019
- Bing-Yuan Cao 0 ,
- Yu-Bin Zhong 1
Foshan University, Foshan, China
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School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
- Presents recent research in fuzzy sets and operations research
- Combines fuzzy mathematics and systems, operation research, management applications, and soft sciences
- Includes papers from the Ninth International Conference on Fuzzy Information and Engineering (ICFIE2017)
Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 872)
Included in the following conference series:
- ICFIE: International Conference on Fuzzy Information & Engineering
Conference proceedings info: ICFIE 2017.
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About this book
This book presents the latest advances in applying fuzzy sets and operations research technology and methods. It is the first fuzzy mathematics textbook for students in high school and technical secondary schools. Part of Springer’s book series: Advances in Intelligent and Soft Computing, it includes the 36 best papers from the Ninth International Conference on Fuzzy Information and Engineering (ICFIE2017), organized by the Fuzzy Information and Engineering Branch of Operations Research Society of China and Operations Research Society of Guangdong Province in China. Every paper has been carefully peer-reviewed by leading experts.
1. Fuzzy Measure and Integral;
3. Classification and Recognition;
4. Control and Fuzziness;
5. Extension of Fuzzy Set and System;
6. Operations Research and Management (OR);
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The Emergence of Fuzzy Sets: A Historical Perspective
Fuzzy Arithmetic for Uncertainty Analysis
Philosophy of Science, Operations Research, and Fuzzy Set Theory – Personal Observations
- Fuzzy Information
- Fuzzy Systems and Mathematics
- Soft Computing
- Artificial Intelligence
- Operation Research
- Control and Fuzziness
- Fuzzy Management and Financial Mathematics
- Fuzzy Mathematics Programming
- Fuzzy Statistics Decision and Forecast
- Big Data and Random Model
Table of contents (36 papers)
Front matter, fuzzy measure and integral, trapezoidal intuitionistic approximations of intuitionistic fuzzy numbers preserving the width.
- Shu-yang Li, Hong-xing Li
New Definition of the Definite Integral of Fuzzy Valued Function Linearly Generated by Structural Elements
- Tian-jun Shu, Zhi-wen Mo
An Information Quantity-Based Uncertainty Measure to Incomplete Numerical Systems
- Xin Guo, Yingzhuo Xiang, Lan Shu
An Inexact Reasoning Method Based on Sugeno Integral
- Jun Shen, De-jun Peng, Sheng-quan Ma
Fuzzy Topology and Algebras
Properties of fuzzy filters in eq-algebras, the \(( \in , \in \vee {q_{_{\left( {\lambda ,\mu } \right) }}}) -\) fuzzy subalgebras of \(ku -\) algebras.
- Liu-hong Chen, Zu-hua Liao, Lun Li, Wei Song, Yong Li, Wei-long Liu et al.
On Derivations of FI-Algebras
- Jian-xiang Rong, Zu-hua Liao, Yue Xi, Wei Song, Lun Li, Yong Li
A New Type Soft Prime Ideal of KU -algebras
- Yue Xi, Zu-hua Liao, Xiao-hao Wang, Xin-meng Chen, Wei Song, Shu-zhong Wu et al.
On \((\in , \in \vee {q_{(\lambda ,\mu )}})\) -fuzzy ideals of KU-algebras
- Lun Li, Zu-hua Liao, Zhen-yu Liao, Liu-hong Chen, Wei Song, Yong Li
The Equivalence Between Stratified L -neighborhood Groups and Stratified L -neighborhood Topological Groups
- Yan-rui Lv, Qiu Jin, Fang-fang Zhao, Ling-qiang Li
On \((\in , {\in }{\vee }{q_{k}})\) -fuzzy Filters in \(R_{0}\) -algebras
- Chun-hui Liu
Classification and Recognition
A classification method by using fuzzy neural network and ensemble learning.
- Shining Ding, Wenyan Song, De-gang Wang, Hong-xing Li
Power Load Pattern Classification Based on Threshold and Cloud Improved Fuzzy Clustering
- Yun-dong Gu, Hong-chao Cheng, Shuang Zhang
The Centrality Analysis of the Fuzzy Technology Innovation Network
- Li-ping Liao, Guang-yu Zhang
Social Network User Feature Recognition Method Based on Weighted Graph and Fuzzy Set
- Juan-li Zheng, Fu-yi Wei, Xiao-feng Hu
A New Classifier Fusion Algorithm and Its Application in Practice
- Zhuang-jian Mo, Sheng-quan Ma
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Editors and affiliations.
Bing-Yuan Cao
Yu-Bin Zhong
Bibliographic Information
Book Title : Fuzzy Sets and Operations Research
Editors : Bing-Yuan Cao, Yu-Bin Zhong
Series Title : Advances in Intelligent Systems and Computing
DOI : https://doi.org/10.1007/978-3-030-02777-3
Publisher : Springer Cham
eBook Packages : Intelligent Technologies and Robotics , Intelligent Technologies and Robotics (R0)
Copyright Information : Springer Nature Switzerland AG 2019
Softcover ISBN : 978-3-030-02776-6 Published: 19 March 2019
eBook ISBN : 978-3-030-02777-3 Published: 18 March 2019
Series ISSN : 2194-5357
Series E-ISSN : 2194-5365
Edition Number : 1
Number of Pages : XIV, 420
Number of Illustrations : 67 b/w illustrations, 24 illustrations in colour
Topics : Computational Intelligence , Artificial Intelligence
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Exploring fuzzy set consensus analysis in IoT resource ranking
Soft computing fuzzy set through knn−ml to identify islanding state of integrated electrical grid at different operational events, environmental uncertainty, resource orchestration and digital transformation: a fuzzy-set qca approach, integrating fuzzy set function into floating catchment area measures: a determination of spatial accessibility of service points, fermatean hesitant fuzzy sets with medical decision making application.
Abstract Fermatean fuzzy set idea obtained by combining fermatean fuzzy sets and hesitant fuzzy sets can be used in practice to simplify the solution of complicated multi-criteria decision-making (MCDM) problems. Initially, the notion of fermatean hesitant fuzzy set is given and the operations related to this concept are presented. Aggregation operators according to fermatean hesitant fuzzy sets are given and basic properties of these operators are studied. To choose the best alternative in practice, a novel MCDM method that is obtained with operators has been created. Finally, an example of infectious diseases was examined to indicate the effectiveness of the suggested techniques.
A Multimodal Retrieval and Ranking Method for Scientific Documents Based on HFS and XLNet
Aiming at the defects of traditional full-text retrieval models in dealing with mathematical expressions, which are special objects different from ordinary texts, a multimodal retrieval and ranking method for scientific documents based on hesitant fuzzy sets (HFS) and XLNet is proposed. This method integrates multimodal information, such as mathematical expression images and context text, as keywords to realize the retrieval of scientific documents. In the image modal, the images of mathematical expressions are recognized, and the hesitancy fuzzy set theory is introduced to calculate the hesitancy fuzzy similarity between mathematical query expressions and the mathematical expressions in candidate scientific documents. Meanwhile, in the text mode, XLNet is used to generate word vectors of the mathematical expression context to obtain the similarity between the query text and the mathematical expression context of the candidate scientific documents. Finally, the multimodal evaluation is integrated, and the hesitation fuzzy set is constructed at the document level to obtain the final scores of the scientific documents and corresponding ranked output. The experimental results show that the recall and precision of this method are 0.774 and 0.663 on the NTCIR dataset, respectively, and the average normalized discounted cumulative gain (NDCG) value of the top-10 ranking results is 0.880 on the Chinese scientific document (CSD) dataset.
Method for Diagnostics and Selection of the Type of Market Structure of Commodity Markets Based on Fuzzy Set Theory
Breast cancer prediction using intuitionistic fuzzy set with analytical hierarchy process with delphi method, an improved fuzzy multi-criteria algorithm for optimizing concentrated solar power (csp) hybridized systems based on pythagorean fuzzy set, mbj-neutrosophic subalgebras and filters in $ be $-algebras.
<abstract><p>The concept of a neutrosophic set, which is a generalization of an intuitionistic fuzzy set and a para consistent set etc., was introduced by F. Smarandache. Since then, it has been studied in various applications. In considering a generalization of the neutrosophic set, Mohseni Takallo et al. used the interval valued fuzzy set as the indeterminate membership function because interval valued fuzzy set is a generalization of a fuzzy set, and introduced the notion of MBJ-neutrosophic sets, and then they applied it to BCK/BCI-algebras. The aim of this paper is to apply the concept of MBJ-neutrosophic sets to a $ BE $-algebra, which is a generalization of a BCK-algebra. The notions of MBJ-neutrosophic subalgebras and MBJ-neutrosophic filters of $ BE $-algebras are introduced and related properties are investigated. The conditions under which the MBJ-neutrosophic set can be a MBJ-neutrosophic subalgebra/filter are searched. Characterizations of MBJ-neutrosophic subalgebras and MBJ-neutrosophic filters are considered. The relationship between an MBJ-neutrosophic subalgebra and an MBJ-neutrosophic filter is established.</p></abstract>
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Provides readers with the foundations of fuzzy mathematics as well as more advanced topics A Modern Introduction to Fuzzy Mathematics provides a concise presentation of fuzzy mathematics., moving from proofs of important results to more advanced topics, like fuzzy algebras, fuzzy graph theory, and fuzzy topologies. The authors take the reader through the development of the field of fuzzy ...
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Fuzzy Sets, Fuzzy Logic and Their Applications 2020. Special Issue Editors. Special Issue Information. Keywords. Published Papers. A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making". Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 54639.
Mathematics, an international, peer-reviewed Open Access journal. ... that ⊤-convergence space with their Fischer diagonal condition just characterizes strong L-topology—a type of fuzzy topology. In this paper, ... The present review forms a new basis for further research on systems' assessment in a fuzzy environment.
Fuzzy theory was initiated by L.A. Zadeh in 1965 with his seminal paper "Fuzzy Sets" [ 1 ]. In the early 1960s, he thought that classical control theory had put too much emphasis on precision and therefore could not handle the complex systems. As early as 1962, he wrote that to handle biological systems "we need a radically different kind ...
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the conclusions and suggests several future research directions. For clarity and easy reference, the abbreviations used in this paper are listed in Table Ⅰ. T. ABLE . Ⅰ A. BBREVIATIONS USED IN THIS PAPER. Abbreviations Details FS Fuzzy system ML-FS Mamdani-Larsen fuzzy system TSK-FS Takagi-Sugeno-Kang fuzzy system GFS Graph fuzzy system ̃
Special Issue Information. Dear Colleagues, The notion of the fuzzy set was introduced by Lotfi A. Zadeh (February 4, 1921-September 6, 2017) in 1965. He is also the founder of fuzzy logic. Since the advent of the notion of the fuzzy set, Zadeh and other researchers have used this important and interesting set and established a great deal of ...
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10 This seems to be a proper area for our purpose, given the areas offered by the bibliometric databases and the nature of contributions by research in fuzzy logic. Note also that compared to engineering and mathematics as possible other areas, the most influential papers in computer science enjoy more citation counts according to the databases.
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Compact, lightweight edition. Dispatched in 3 to 5 business days. Free shipping worldwide - see info. This book presents recent research in Fuzzy Sets and Operations Research, combines fuzzy mathematics and systems, operation research, management application and soft sciences, and contains articles from the Ninth International Conference on ...
Mcdm Method. Abstract Fermatean fuzzy set idea obtained by combining fermatean fuzzy sets and hesitant fuzzy sets can be used in practice to simplify the solution of complicated multi-criteria decision-making (MCDM) problems. Initially, the notion of fermatean hesitant fuzzy set is given and the operations related to this concept are presented.
In the 1950s, the mathematically oriented electrical engineer, Lotfi A. Zadeh, investigated system theory, and in the mid-1960s, he established the theory of Fuzzy sets and systems based on the mathematical theorem of linear separability and the pattern classification problem. Contemporaneously, the psychologist, Frank Rosenblatt, developed the theory of the perceptron as a pattern recognition ...
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