Fuzzy Sets and Their Extensions: Representation, Aggregation and Models: Intelligent Systems from Decision Making to Data Mining, Web Intelligence and

ISBN-13: 9783642092909 / Angielski / Miękka / 2010 / 674 str.

Humberto Bustince; Francisco Herrera; Javier Montero

Opis

Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision Fuzzy sets are now more than 40 years old, and have come of age. However, the development of fuzzy set theory at the theoretical level, and its successful appli- tions to science and technology have often run in isolation. Only a little part of the theoretical apparatus was effectively used in past applications. The most prominent ones, namely fuzzy rule-based modeling and control engineering, were directly - spired from a seminal paper by Lot? Zadeh in 1973, suggesting how to use expert knowledge for synthetizing control laws, and from the ?rst experiments published by Abe Mamdani. Later in the eighties, when spectacular applications were bl- soming in Japan, fuzzy rule-based systems were systematized and simpli?ed by Michio Sugeno and colleagues, and became a basic approach to non-linear system modeling and control, soon hybridized with neural networks in the nineties. Thus fuzzy systems signi?cantly contributed to the raise of computational intelligence, and a lot of learning techniques for the construction of (supposedly interpretable) fuzzy models from data were developed under the ?ag of soft computing. Even if this area was quite successful, it is patent that the role, in the success of fuzzy logic, of new fuzzy set-related concepts developed quite at the same time in themathematicalnicheofthefuzzyset communitywaslimited.

Spis treści

Foundations: Representation and Aggregation.- Type-2 Fuzzy Logic and the Modelling of Uncertainty.- My Personal View on Intuitionistic Fuzzy Sets Theory.- Hybridization of Fuzzy and Rough Sets: Present and Future.- An Overview of Computing with Words using Label Semantics.- On the Construction of Models Based on Fuzzy Measures and Integrals.- Interpolatory Type Construction of General Aggregation Operators.- A Review of Aggregation Functions.- Identification of Weights in Aggregation Operators.- Linguistic Aggregation Operators: An Overview.- Aggregation Operators in Interval-valued Fuzzy and Atanassov’s Intuitionistic Fuzzy Set Theory.- From Decision Making to Data Mining, Web Intelligence and Computer Vision.- Fuzzy Preference Modelling: Fundamentals and Recent Advances.- Preferences and Consistency Issues in Group Decision Making.- Fuzzy Set Extensions of the Dominance-Based Rough Set Approach.- On Group Decision Making, Consensus Reaching, Voting and Voting Paradoxes under Fuzzy Preferences and a Fuzzy Majority: A Survey and some Perspectives.- Extension of Some Voting Systems to the Field of Gradual Preferences.- A Linguistic Decision Based Model Applied to Olive Oil Sensory Evaluation.- Atanassov’s Intuitionistic Fuzzy Sets as a Promising Tool for Extended Fuzzy Decision Making Models.- Fuzzy Methods for Data Mining and Machine Learning: State of the Art and Prospects.- Pattern Classification with Linguistic Rules.- An Overview of Mining Fuzzy Association Rules.- Subgroup Discovery with Linguistic Rules.- Fuzzy Prototypes: From a Cognitive View to a Machine Learning Principle.- Improving Fuzzy Classification by Means of a Segmentation Algorithm.- FIS2JADE: A New Vista for Fuzzy-oriented Agents.- An Overview on the Approximation Quality Based on Rough-Fuzzy Hybrids.- Fuzzy Sets in Information Retrieval: State of the Art and Research Trends.- Fuzzy Sets and Web Meta-search Engines.- Fuzzy Set Techniques in E-Service Applications.- A Fuzzy Linguistic Recommender System to Advice Research Resources in University Digital Libraries.- Fuzzy Measures in Image Processing.- Type II Fuzzy Image Segmentation.- Image Threshold Computation by Modelizing Knowledge/Unknowledge by Means of Atanassov’s Intuitionistic Fuzzy Sets.- Colour Image Comparison Using Vector Operators.- A Fuzzy-based Automated Cells Detection System for Color Pap Smear Tests –-FACSDS–.

Blurb

This carefully edited book presents an up-to-date state of current research in the use of fuzzy sets and their extensions, paying attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modelling and solving problems.

The book contains 34 chapters divided into two parts. The first part is divided into two sections. Section 1 contains four review papers introducing some non standard representations that extend fuzzy sets (type-2 fuzzy sets, Atanassov’s IFS, fuzzy rough sets and computing with words under the fuzzy sets perspective). Section 2 reviews different aggregation issues from a theoretical and practical point of view; this second part is divided into four sections. Section 3 is devoted to decision making, with seven papers that show how fuzzy sets and their extensions are an important tool for modelling choice problems. Section 4 includes eight papers that cover different aspects on the use of fuzzy sets and their extensions in data mining, giving an illustrative review of the state of the art on the topic. Section 5 is devoted to the emergent topic of web intelligence and contains four papers that show the use of fuzzy sets theory in some problems that can be tackled in this topic. Section 6 is devoted to the use of fuzzy sets and their extensions in the field of computer vision, suggesting how these can be an useful tool in this area.

This volume will be extremely useful to any non-expert reader who is keen to get a good overview on the latest developments in this research field. It will also support those specialists who wish to discover the latest results and trends in the abovementioned areas.