Granular, Fuzzy, and Soft Computing

2023-03-29
Granular, Fuzzy, and Soft Computing

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  • Author: Tsau-Young Lin
  • Publisher: Springer Nature
  • ISBN: 1071626280
  • Category : Mathematics
  • Languages : en
  • Pages : 936

The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.

Granular, Soft and Fuzzy Approaches for Intelligent Systems

2016-11-14
Granular, Soft and Fuzzy Approaches for Intelligent Systems

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  • Author: Janusz Kacprzyk
  • Publisher: Springer
  • ISBN: 3319403141
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 248

This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communities. It has been motivated by the authors’ appreciation of his original thinking and groundbreaking ideas, with a special thought to his valuable research on the computerized implementation of various aspects of human cognition for decision-making and problem-solving.

Granular Computing

2018-09-03
Granular Computing

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  • Author: Witold Pedrycz
  • Publisher: CRC Press
  • ISBN: 135183262X
  • Category : Computers
  • Languages : en
  • Pages : 313

Information granules, as encountered in natural language, are implicit in nature. To make them fully operational so they can be effectively used to analyze and design intelligent systems, information granules need to be made explicit. An emerging discipline, granular computing focuses on formalizing information granules and unifying them to create a coherent methodological and developmental environment for intelligent system design and analysis. Granular Computing: Analysis and Design of Intelligent Systems presents the unified principles of granular computing along with its comprehensive algorithmic framework and design practices. Introduces the concepts of information granules, information granularity, and granular computing Presents the key formalisms of information granules Builds on the concepts of information granules with discussion of higher-order and higher-type information granules Discusses the operational concept of information granulation and degranulation by highlighting the essence of this tandem and its quantification in terms of the associated reconstruction error Examines the principle of justifiable granularity Stresses the need to look at information granularity as an important design asset that helps construct more realistic models of real-world systems or facilitate collaborative pursuits of system modeling Highlights the concepts, architectures, and design algorithms of granular models Explores application domains where granular computing and granular models play a visible role, including pattern recognition, time series, and decision making Written by an internationally renowned authority in the field, this innovative book introduces readers to granular computing as a new paradigm for the analysis and synthesis of intelligent systems. It is a valuable resource for those engaged in research and practical developments in computer, electrical, industrial, manufacturing, and biomedical engineering. Building from fundamentals, the book is also suitable for readers from nontechnical disciplines where information granules assume a visible position.

Granular Computing: At the Junction of Rough Sets and Fuzzy Sets

2008-02-20
Granular Computing: At the Junction of Rough Sets and Fuzzy Sets

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  • Author: Rafael Bello
  • Publisher: Springer Science & Business Media
  • ISBN: 3540769722
  • Category : Computers
  • Languages : en
  • Pages : 339

Since their very inception, both fuzzy and rough set theories have earned a sound, well-deserved reputation owing to their intrinsic capabilities to model uncertainty coming from the real world. The increasing amount of investigations on both subjects reported every year in the literature vouches for the dynamics of the area and its rapid advancements. In the last few years the widespread utilization of fuzzy and rough sets as granulation sources has contributed to lay both methodologies in a privileged position within Granular Computing, thus giving rise to a sort a modeling which is far closer to the way human beings perceive their environment – via granulated knowledge. This volume is a compilation of the best papers presented at the First International Symposium on Fuzzy and Rough Sets (ISFUROS 2006) held in Santa Clara, Cuba. You will therefore find valuable contributions both in the theoretical field as in several application domains such as intelligent control, data analysis, decision making and machine learning, just to name a few. Together, they will catch you up with the huge potential of the aforementioned methodologies.

Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

2016-02-23
Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

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  • Author: Daniela Sanchez
  • Publisher: Springer
  • ISBN: 3319288628
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 101

In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.

Handbook of Granular Computing

2008-07-31
Handbook of Granular Computing

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  • Author: Witold Pedrycz
  • Publisher: John Wiley & Sons
  • ISBN: 0470724153
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 1148

Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field. Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies. Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies. Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies. Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts. The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics.

Decision Making and Soft Computing

2014-07-07
Decision Making and Soft Computing

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  • Author: Ronei Marcos de Moraes
  • Publisher: World Scientific
  • ISBN: 9814623008
  • Category : Computers
  • Languages : en
  • Pages : 780

FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the 11th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view. Contents:Invited Lectures:The Contribution of Fuzzy Sets to Decision Sciences (D Dubois)Granular Fuzzy Systems: A New Direction in Soft Computing and Human Centric Decision-Making (Witold Pedrycz)Some Approaches Towards Lattice Computing in Mathematical Morphology and Computational Intelligence (Peter Sussner)Decision Making and Decision Support SystemsStatistics, Data Analysis and Data MiningFoundations of Computational IntelligenceSoft Computing and Applied ResearchIntelligent Systems and Knowledge EngineeringUncertainty ModelingIntelligent Information Processing Readership: Graduate students, researchers, and academics in artificial intelligence/machine learning, information management, decision sciences, databases/information sciences and fuzzy logic. Keywords:FLINS 2014;Soft Computing;Knowledge Engineering;Decision Making

Quantitative Logic and Soft Computing

2012
Quantitative Logic and Soft Computing

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  • Author: Guojun Wang
  • Publisher: World Scientific
  • ISBN: 9814401528
  • Category : Computers
  • Languages : en
  • Pages : 724

The QL&SC 2012 is a major symposium for scientists, and practitioners all around the world to present their latest reseaches, results, ideas, developments and applications in such areas as quantitative logic, many-valued logic, fuzzy logic, quantification of software, artificial intelligence, fuzzy sets and systems and soft computing. This invaluable book provides a broad introduction to the fuzzy reasoning and soft computing. It is certain one should not go too far in approximation and optimization, and a certain degree must be kept in mind. This is the essential idea of quantitative logic and soft computing. The explanations in the book are complete to provide the necessary background material needed to go further into the subject and explore the research literature. It is suitable reading for graduate students. It provides a platform for mutual exchanges from top experts and scholars around the world in this field.

Quantitative Logic and Soft Computing

2012
Quantitative Logic and Soft Computing

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  • Author: Yongming Li
  • Publisher: World Scientific
  • ISBN: 9814401536
  • Category : Computers
  • Languages : en
  • Pages : 724

The QL&SC 2012 is a major symposium for scientists, and practitioners all around the world to present their latest researches, results, ideas, developments and applications in such areas as quantitative logic, many-valued logic, fuzzy logic, quantification of software, artificial intelligence, fuzzy sets and systems and soft computing. This invaluable book provides a broad introduction to the fuzzy reasoning and soft computing. It is certain one should not go too far in approximation and optimization, and a certain degree must be kept in mind. This is the essential idea of quantitative logic and soft computing. The explanations in the book are complete to provide the necessary background material needed to go further into the subject and explore the research literature. It is suitable reading for graduate students. It provides a platform for mutual exchanges from top experts and scholars around the world in this field.

Pattern Recognition Algorithms for Data Mining

2004-05-27
Pattern Recognition Algorithms for Data Mining

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  • Author: Sankar K. Pal
  • Publisher: CRC Press
  • ISBN: 1135436401
  • Category : Computers
  • Languages : en
  • Pages : 275

Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.