Fuzzy Sets, Rough Sets, Multisets and Clustering

Fuzzy Sets, Rough Sets, Multisets and Clustering PDF Author: Vicenç Torra
Publisher: Springer
ISBN: 3319475576
Category : Technology & Engineering
Languages : en
Pages : 336

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Book Description
This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.

Fuzzy Sets, Rough Sets, Multisets and Clustering

Fuzzy Sets, Rough Sets, Multisets and Clustering PDF Author: Vicenç Torra
Publisher: Springer
ISBN: 3319475576
Category : Technology & Engineering
Languages : en
Pages : 336

Get Book Here

Book Description
This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.

Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review PDF Author: Pierpaolo D’Urso
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 33

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Book Description
Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory.

Thriving Rough Sets

Thriving Rough Sets PDF Author: Guoyin Wang
Publisher: Springer
ISBN: 3319549669
Category : Technology & Engineering
Languages : en
Pages : 433

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Book Description
This special book is dedicated to the memory of Professor Zdzisław Pawlak, the father of rough set theory, in order to commemorate both the 10th anniversary of his passing and 35 years of rough set theory. The book consists of 20 chapters distributed into four sections, which focus in turn on a historical review of Professor Zdzisław Pawlak and rough set theory; a review of the theory of rough sets; the state of the art of rough set theory; and major developments in rough set based data mining approaches. Apart from Professor Pawlak’s contributions to rough set theory, other areas he was interested in are also included. Moreover, recent theoretical studies and advances in applications are also presented. The book will offer a useful guide for researchers in Knowledge Engineering and Data Mining by suggesting new approaches to solving the problems they encounter.

Rough Sets

Rough Sets PDF Author: Víctor Flores
Publisher: Springer
ISBN: 3319471600
Category : Computers
Languages : en
Pages : 596

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Book Description
This book constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2016, held in Santiago de Chile, Chile, in October 2016. The 46 revised full papers presented together with 7 keynotes, tutorials and expert papers were carefully reviewed and selected from 108 submissions. The papers are grouped in topical sections on Rough Sets, Approximation and Granulation; Rough Sets, Non-Determinism and Incompleteness; Rough Sets and Three-way Decisions; Fuzziness and Similarity in Knowledge Representation; Machine Learning and Decision Making; Ranking and Clustering; Derivation and Application of Rules and Trees; Derivation and Application of Feature Subsets.

Topics in Rough Set Theory

Topics in Rough Set Theory PDF Author: Seiki Akama
Publisher: Springer Nature
ISBN: 3030295664
Category : Technology & Engineering
Languages : en
Pages : 208

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Book Description
This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.

Transactions on Rough Sets II

Transactions on Rough Sets II PDF Author: James F. Peters
Publisher: Springer
ISBN: 3540277781
Category : Computers
Languages : en
Pages : 371

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Book Description
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, starting from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness and incompleteness, such as fuzzy sets and theory of evidence. This second volume of the Transactions on Rough Sets presents 17 thoroughly reviewed revised papers devoted to rough set theory, fuzzy set theory; these papers highlight important aspects of these theories, their interrelation and application in various fields.

Advances in Fuzzy Logic and Technology 2017

Advances in Fuzzy Logic and Technology 2017 PDF Author: Janusz Kacprzyk
Publisher: Springer
ISBN: 3319668277
Category : Technology & Engineering
Languages : en
Pages : 613

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Book Description
This volume constitutes the proceedings of two collocated international conferences: EUSFLAT-2017 – the 10th edition of the flagship Conference of the European Society for Fuzzy Logic and Technology held in Warsaw, Poland, on September 11–15, 2017, and IWIFSGN’2017 – The Sixteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, held in Warsaw on September 13–15, 2017. The conferences were organized by the Systems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and the Polish Operational and Systems Research Society in collaboration with the European Society for Fuzzy Logic and Technology (EUSFLAT), the Bulgarian Academy of Sciences and various European universities. The aim of the EUSFLAT-2017 was to bring together theoreticians and practitioners working on fuzzy logic, fuzzy systems, soft computing and related areas and to provide a platform for exchanging ideas and discussing the l atest trends and ideas, while the aim of IWIFSGN’2017 was to discuss new developments in extensions of the concept of a fuzzy set, such as an intuitionistic fuzzy set, as well as other concepts, like that of a generalized net. The papers included, written by leading international experts, as well as the special sessions and panel discussions contribute to the development the field, strengthen collaborations and intensify networking.

Industrial Engineering in the Internet-of-Things World

Industrial Engineering in the Internet-of-Things World PDF Author: Fethi Calisir
Publisher: Springer Nature
ISBN: 3030767248
Category : Technology & Engineering
Languages : en
Pages : 486

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Book Description
This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), organized virtually on August 14–15, 2020, by Istanbul Technical University. It covers a wide range of topics, including decision analysis, supply chain management, systems modelling and quality control. Further, special emphasis is placed on cutting-edge applications of industrial Internet-of-Things. Technological, economic and business challenges are discussed in detail, presenting effective strategies that can be used to modernize current structures, eliminating the barriers that are keeping industries from taking full advantage of IoT technologies. The book offers an important link between technological research and industry best practices, and covers various disciplinary areas such as manufacturing, healthcare and service engineering, among others.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems PDF Author: Marie-Jeanne Lesot
Publisher: Springer Nature
ISBN: 3030501434
Category : Computers
Languages : en
Pages : 816

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Book Description
This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems PDF Author: Davide Ciucci
Publisher: Springer Nature
ISBN: 3031089715
Category : Computers
Languages : en
Pages : 825

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Book Description
This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.