Fuzzy Logic in Intelligent System Design : Theory and Applications.
Melin, Patricia.; Castillo, Oscar.; Kacprzyk, Janusz.; Reformat, Marek.; Melek, William.
2017
TA1-2040
Available Online

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Title Fuzzy Logic in Intelligent System Design : Theory and Applications.
Author Melin, Patricia.
ISBN 9783319671376
3319671375
3319671367
9783319671369
DOI https://doi.org/10.1007/978-3-319-67137-6
Publication Details Cham : Springer International Publishing, 2017.
Language English
Description 1 online resource (420 pages).
Item Number 10.1007/978-3-319-67137-6 doi
Call Number TA1-2040
Dewey Decimal Classification 620
Summary This book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new concepts and algorithms for type-2 fuzzy systems, and on applications of type-2 fuzzy systems in diverse areas, such as time series prediction and pattern recognition. In turn, the third part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques describing new nature-inspired optimization algorithms that use fuzzy dynamic adaptation of parameters. The fourth part presents emergent intelligent models, which range from quantum algorithms to cellular automata. The fifth part explores applications of fuzzy logic in diverse areas of medicine, such as the diagnosis of hypertension and heart diseases. The sixth part describes new computational intelligence algorithms and their applications in different areas of intelligent control, while the seventh examines the use of fuzzy logic in different mathematic models. The eight part deals with a diverse range of applications of fuzzy logic, ranging from environmental to autonomous navigation, while the ninth covers theoretical concepts of fuzzy models.
Note 5 Conclusion.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Description based on print version record.
Added Author Castillo, Oscar.
Kacprzyk, Janusz.
Reformat, Marek.
Melek, William.
Series Advances in intelligent systems and computing.
Available in Other Form Fuzzy Logic in Intelligent System Design : Theory and Applications.
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Preface; Contents; Theoretical Aspects of Fuzzy Logic; Can Multi-constraint Fuzzy Optimization Bring Complex Problems in Selecting Optimal Solar Power Generating System into Focus?; Abstract; 1 Introduction; 1.1 Commentary on Solar Power Generating System and Selection; 1.2 Objective; 2 Case Study; 2.1 Expert Knowledgebase; 3 Results and Discussion; 3.1 Similarity Between Experts; 3.2 Multi Constraint Fuzzy Optimization; References; Relating Fuzzy Set Similarity Measures; Abstract; 1 Introduction; 2 Respects for Similarity; 3 Set-Based Similarity; 4 Geometric-Based Similarity.

5 Relating Set and Geometric Similarity6 Conclusions; References; Correlation Measures for Bipolar Rating Profiles; Abstract; 1 Introduction; 2 Finite Bipolar Rating Scales and Bipolar Scoring Functions; 3 General Methods of Construction of Correlation Measures on the Set with Involution; 4 Correlation Measures on the Set of Bipolar Rating Profiles; 5 Conclusions; Acknowledgements; References; Solving Real-World Fuzzy Quadratic Programming Problems by Dual Parametric Approach; Abstract; 1 Introduction; 2 Dual Parametric Approach in Fuzzy Environment; 3 Economic Dispatch Problem.

3.1 Numerical Results and Analysis4 Conclusion; Acknowledgment; References; Type-2 Fuzzy Logic; A Type-2 Fuzzy Hybrid Expert System for Commercial Burglary; Abstract; 1 Introduction; 2 Fuzzy Systems; 3 Problem Description; 4 Designing the Type-2 FLS; 4.1 Determination of Input and Output Variables; 4.2 Feature Selection; 4.3 Determination of the Number of Rules and Clustering the Output Space; 4.4 Projection of Membership Functions of Output onto Input Spaces; 4.5 Tuning the Parameters of Type-1 Membership Functions; 4.6 Transformation Type-1 to Interval Type-2 Membership Functions.

4.7 Tuning the Parameters of Interval Type-2 Membership Functions5 The Proposed IT2 Fuzzy Hybrid Expert System; 6 Performance Evaluation; 7 Conclusion; References; A Type-2 Fuzzy Expert System for Diagnosis of Leukemia; Abstract; 1 Introduction; 1.1 Leukemia; 1.2 Expert System; 1.3 Type-2 Fuzzy; 2 Literature Review; 3 Methodology; 3.1 Leukemia Dataset; 3.2 Determining the Number of Rules; 3.3 The Proposed Type-2 Fuzzy Model; 3.4 Performance Evaluation; 4 Conclusion; References.

Comparative Study of Metrics That Affect in the Performance of the Bee Colony Optimization Algorithm Through Interval Type-2 Fuzzy Logic SystemsAbstract; 1 Introduction; 2 Background; 3 Interval Type-2 Fuzzy Systems; 3.1 Fuzzy Logic Controller; 4 Proposed Methods; 5 Simulations Results; 6 Discussion; 7 Conclusions; References; Type-2 Fuzzy Approach in Multi Attribute Group Decision Making Problem; Abstract; 1 Introduction; 2 Basic Concepts of Type2 Fuzzy Sets; 2.1 Linguistic Weighted Averaging for T2-FSs; 3 Proposed Type-2 Fuzzy Multi Attribute Group Decision Making; 4 An Illustrative Example.

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