Ebook: Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

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.

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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.

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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.

Content:
Front Matter....Pages I-XX
Front Matter....Pages 1-1
Type-2 Fuzzy Logic and the Modelling of Uncertainty....Pages 3-22
My Personal View on Intuitionistic Fuzzy Sets Theory....Pages 23-43
Hybridization of Fuzzy and Rough Sets: Present and Future....Pages 45-64
An Overview of Computing with Words using Label Semantics....Pages 65-87
On the Construction of Models Based on Fuzzy Measures and Integrals....Pages 89-97
Interpolatory Type Construction of General Aggregation Operators....Pages 99-120
A Review of Aggregation Functions....Pages 121-144
Identification of Weights in Aggregation Operators....Pages 145-162
Linguistic Aggregation Operators: An Overview....Pages 163-181
Aggregation Operators in Interval-valued Fuzzy and Atanassov’s Intuitionistic Fuzzy Set Theory....Pages 183-203
Front Matter....Pages 205-205
Fuzzy Preference Modelling: Fundamentals and Recent Advances....Pages 207-217
Preferences and Consistency Issues in Group Decision Making....Pages 219-237
Fuzzy Set Extensions of the Dominance-Based Rough Set Approach....Pages 239-261
On Group Decision Making, Consensus Reaching, Voting and Voting Paradoxes under Fuzzy Preferences and a Fuzzy Majority: A Survey and some Perspectives....Pages 263-295
A Linguistic Decision Based Model Applied to Olive Oil Sensory Evaluation....Pages 297-315
Atanassov’s Intuitionistic Fuzzy Sets as a Promising Tool for Extended Fuzzy Decision Making Models....Pages 317-334
Pattern Classification with Linguistic Rules....Pages 335-355
An Overview of Mining Fuzzy Association Rules....Pages 357-375
Front Matter....Pages 377-395
Subgroup Discovery with Linguistic Rules....Pages 397-410
Fuzzy Prototypes: From a Cognitive View to a Machine Learning Principle....Pages 205-205
Improving Fuzzy Classification by Means of a Segmentation Algorithm....Pages 411-430
FIS2JADE: A New Vista for Fuzzy-oriented Agents....Pages 431-452
An Overview on the Approximation Quality Based on Rough-Fuzzy Hybrids....Pages 453-471
Fuzzy Sets in Information Retrieval: State of the Art and Research Trends....Pages 473-491
Fuzzy Sets and Web Meta-search Engines....Pages 493-515
Fuzzy Set Techniques in E-Service Applications....Pages 517-535
A Fuzzy Linguistic Recommender System to Advice Research Resources in University Digital Libraries....Pages 537-552
Fuzzy Measures in Image Processing....Pages 553-566
Type II Fuzzy Image Segmentation....Pages 567-585
Image Threshold Computation by Modelizing Knowledge/Unknowledge by Means of Atanassov’s Intuitionistic Fuzzy Sets....Pages 587-606
Colour Image Comparison Using Vector Operators....Pages 607-619
A Fuzzy-based Automated Cells Detection System for Color Pap Smear Tests –-FACSDS–....Pages 621-638
....Pages 639-656