Ebook: Computing with Words in Information/Intelligent Systems 2: Applications

The volume is the first one in the world literature which is a comprehensive, up to date account on computing with words, a new direction in broadly perceived intelligent systems, proposed and advocated by Professor Zadeh, the founder of fuzzy sets theory and fuzzy logic. Historically, computing was focused on manipulation of numbers. However, in recent years it became more and more obvious that computing had been encompassing not only this, but also manipulation on signal, sounds, images and text; the latter aspects of computing are becoming more and more relevant. However, the traditional manipulation of text (e.g., machine translation, spell checking, etc.) does not cover the mainstream of computing with words, mainly the representation and manipulation of propositions from natural language describing operations and relations. Such problems cannot be solved by conventional methods of logic, probability theory and numerical analysis. Fuzzy logic is shown to be an effective tool to handle such problems.
Computing with words may form a basis of a computational theory of perceptions inspired by a remarkable human ability to perform a wide variety of tasks just on the basis of vague and imprecise information expressed in natural language.
In Part 2 applications in a wide array of fields are presented which use the paradigm of computing with words, exemplified by reasoning, data anaylsis, data mining, machine learning, risk anaylses, reliability and quality control, decision making, optimization and control, databases, medical diagnosis, business analyses, traffic management, power system planning, military applications, etc.

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The volume is the first one in the world literature which is a comprehensive, up to date account on computing with words, a new direction in broadly perceived intelligent systems, proposed and advocated by Professor Zadeh, the founder of fuzzy sets theory and fuzzy logic. Historically, computing was focused on manipulation of numbers. However, in recent years it became more and more obvious that computing had been encompassing not only this, but also manipulation on signal, sounds, images and text; the latter aspects of computing are becoming more and more relevant. However, the traditional manipulation of text (e.g., machine translation, spell checking, etc.) does not cover the mainstream of computing with words, mainly the representation and manipulation of propositions from natural language describing operations and relations. Such problems cannot be solved by conventional methods of logic, probability theory and numerical analysis. Fuzzy logic is shown to be an effective tool to handle such problems.
Computing with words may form a basis of a computational theory of perceptions inspired by a remarkable human ability to perform a wide variety of tasks just on the basis of vague and imprecise information expressed in natural language.
In Part 2 applications in a wide array of fields are presented which use the paradigm of computing with words, exemplified by reasoning, data anaylsis, data mining, machine learning, risk anaylses, reliability and quality control, decision making, optimization and control, databases, medical diagnosis, business analyses, traffic management, power system planning, military applications, etc.

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The volume is the first one in the world literature which is a comprehensive, up to date account on computing with words, a new direction in broadly perceived intelligent systems, proposed and advocated by Professor Zadeh, the founder of fuzzy sets theory and fuzzy logic. Historically, computing was focused on manipulation of numbers. However, in recent years it became more and more obvious that computing had been encompassing not only this, but also manipulation on signal, sounds, images and text; the latter aspects of computing are becoming more and more relevant. However, the traditional manipulation of text (e.g., machine translation, spell checking, etc.) does not cover the mainstream of computing with words, mainly the representation and manipulation of propositions from natural language describing operations and relations. Such problems cannot be solved by conventional methods of logic, probability theory and numerical analysis. Fuzzy logic is shown to be an effective tool to handle such problems.
Computing with words may form a basis of a computational theory of perceptions inspired by a remarkable human ability to perform a wide variety of tasks just on the basis of vague and imprecise information expressed in natural language.
In Part 2 applications in a wide array of fields are presented which use the paradigm of computing with words, exemplified by reasoning, data anaylsis, data mining, machine learning, risk anaylses, reliability and quality control, decision making, optimization and control, databases, medical diagnosis, business analyses, traffic management, power system planning, military applications, etc.
Content:
Front Matter....Pages I-IX
Front Matter....Pages 1-1
Neural Fuzzy Intelligent Agents....Pages 3-34
Neuro Fuzzy Systems for Data Analysis....Pages 35-74
A New Fuzzy Inference System Based on Artificial Neural Network and Its Applications....Pages 75-94
Encouraging Cooperation in the Genetic Iterative Rule Learning Approach for Qualitative Modeling....Pages 95-117
Front Matter....Pages 119-119
Fuzzy Graphs with Linguistic Inputs-Outputs by Fuzzy Approximation Models....Pages 121-136
Fuzzy Random Variables: Modeling Linguistic Statistical Data....Pages 137-157
Front Matter....Pages 159-159
Linguistic Model of System Reliability Analysis....Pages 161-175
Lifetime Tests for Vague Data....Pages 176-193
Systems Analytic Models for Fuzzy Risk Estimation....Pages 195-220
Front Matter....Pages 221-221
Decision Analysis by Advanced Fuzzy Systems....Pages 223-242
Group Decision Making and a Measure of Consensus under Fuzzy Preferences and a Fuzzy Linguistic Majority....Pages 243-269
Linear Programming with Words....Pages 270-288
Computing with Words in Control....Pages 289-304
On Linguistic Fuzzy Constraint Satisfaction Problems....Pages 305-321
Front Matter....Pages 323-323
Data Models for Dealing with Linguistic and Imprecise Information....Pages 325-344
Fuzzy Set Approaches to Model Uncertainty in Spatial Data and Geographic Information Systems....Pages 345-367
Computing Fuzzy Dependencies with Linguistic Labels....Pages 368-382
The Paradigm of Computing with Words in Intelligent Database Querying....Pages 383-398
Linguistic Data Mining....Pages 399-420
Evaluation of Connectionist Information Retrieval in a Legal Document Collection....Pages 421-434
Front Matter....Pages 435-435
Using Linguistic Models in Medical Decision Making....Pages 437-458
The Fuzzy Logic Advisor for Social Judgments: A First Attempt....Pages 459-483
Conceptualisation with GABEK: Ideas on Social Change in South Africa....Pages 484-499
A Linguistic Decision Model to Suppliers Selection in International Purchasing....Pages 500-524
Fuzzy System for Air Traffic Flow Management....Pages 525-547
A Fuzzy Approach to Contracting Electrical Energy in Competitive Electricity Markets....Pages 548-566
Fuzzy Logic and Intelligent Computing in Nuclear Engineering....Pages 567-585
Computational Intelligence Techniques in Landmine Detection....Pages 586-609
Back Matter....Pages 610-610

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The volume is the first one in the world literature which is a comprehensive, up to date account on computing with words, a new direction in broadly perceived intelligent systems, proposed and advocated by Professor Zadeh, the founder of fuzzy sets theory and fuzzy logic. Historically, computing was focused on manipulation of numbers. However, in recent years it became more and more obvious that computing had been encompassing not only this, but also manipulation on signal, sounds, images and text; the latter aspects of computing are becoming more and more relevant. However, the traditional manipulation of text (e.g., machine translation, spell checking, etc.) does not cover the mainstream of computing with words, mainly the representation and manipulation of propositions from natural language describing operations and relations. Such problems cannot be solved by conventional methods of logic, probability theory and numerical analysis. Fuzzy logic is shown to be an effective tool to handle such problems.
Computing with words may form a basis of a computational theory of perceptions inspired by a remarkable human ability to perform a wide variety of tasks just on the basis of vague and imprecise information expressed in natural language.
In Part 2 applications in a wide array of fields are presented which use the paradigm of computing with words, exemplified by reasoning, data anaylsis, data mining, machine learning, risk anaylses, reliability and quality control, decision making, optimization and control, databases, medical diagnosis, business analyses, traffic management, power system planning, military applications, etc.
Content:
Front Matter....Pages I-IX
Front Matter....Pages 1-1
Neural Fuzzy Intelligent Agents....Pages 3-34
Neuro Fuzzy Systems for Data Analysis....Pages 35-74
A New Fuzzy Inference System Based on Artificial Neural Network and Its Applications....Pages 75-94
Encouraging Cooperation in the Genetic Iterative Rule Learning Approach for Qualitative Modeling....Pages 95-117
Front Matter....Pages 119-119
Fuzzy Graphs with Linguistic Inputs-Outputs by Fuzzy Approximation Models....Pages 121-136
Fuzzy Random Variables: Modeling Linguistic Statistical Data....Pages 137-157
Front Matter....Pages 159-159
Linguistic Model of System Reliability Analysis....Pages 161-175
Lifetime Tests for Vague Data....Pages 176-193
Systems Analytic Models for Fuzzy Risk Estimation....Pages 195-220
Front Matter....Pages 221-221
Decision Analysis by Advanced Fuzzy Systems....Pages 223-242
Group Decision Making and a Measure of Consensus under Fuzzy Preferences and a Fuzzy Linguistic Majority....Pages 243-269
Linear Programming with Words....Pages 270-288
Computing with Words in Control....Pages 289-304
On Linguistic Fuzzy Constraint Satisfaction Problems....Pages 305-321
Front Matter....Pages 323-323
Data Models for Dealing with Linguistic and Imprecise Information....Pages 325-344
Fuzzy Set Approaches to Model Uncertainty in Spatial Data and Geographic Information Systems....Pages 345-367
Computing Fuzzy Dependencies with Linguistic Labels....Pages 368-382
The Paradigm of Computing with Words in Intelligent Database Querying....Pages 383-398
Linguistic Data Mining....Pages 399-420
Evaluation of Connectionist Information Retrieval in a Legal Document Collection....Pages 421-434
Front Matter....Pages 435-435
Using Linguistic Models in Medical Decision Making....Pages 437-458
The Fuzzy Logic Advisor for Social Judgments: A First Attempt....Pages 459-483
Conceptualisation with GABEK: Ideas on Social Change in South Africa....Pages 484-499
A Linguistic Decision Model to Suppliers Selection in International Purchasing....Pages 500-524
Fuzzy System for Air Traffic Flow Management....Pages 525-547
A Fuzzy Approach to Contracting Electrical Energy in Competitive Electricity Markets....Pages 548-566
Fuzzy Logic and Intelligent Computing in Nuclear Engineering....Pages 567-585
Computational Intelligence Techniques in Landmine Detection....Pages 586-609
Back Matter....Pages 610-610
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