About Book

Fuzzy sets are sets whose elements have degrees of membership. Application of fuzzy set theory has rapidly increased with establishing its utility in numerous areas of the scientific world. Any system consisting of vague and ambiguous input variables may contribute to an ultimate effect. Fuzzy sets emphasizes on the applications of fuzzy technology in artificial intelligence, computer science, control engineering, decision theory, expert systems, logic, management science, operations research, robotics, and other. An important issue in the theory of fuzzy sets that does not have a counterpart in the theory of crisp sets relates to the combination of fuzzy sets through disjunction and conjunction or, equivalently, union and intersection. Since its inception, the theory has matured into a wide-ranging collection of concepts and techniques for dealing with complex phenomena that do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. The book aims to shed light on some of the unexplored aspects of fuzzy sets. It talks in detail about the various techniques and methods used in this medium of study. It deals with finite element method, clinical application, fuzzy logic approach, fuzzy logic controller and standard fuzzy sets. It also explores risk analysis, fuzzy rule base, fuzzy self-tuning PID, image analysis, modelling driving forces and geographic classification. The topics included in it are of utmost significance and are bound to provide incredible insights to readers. Different approaches, evaluations and methodologies have been included in it. It will serve as a valuable source of reference for those interested in this field.

Preface............................................................................................................v

Chapter 1 A Fuzzy Rule Based Approach to Geographic Classification of Virgin Olive Oil Using T-Operators......................................................1

Abstract...................................................................................................1

1. Introduction............................................................................................2

2. Geographic classification problem.....................................................4

3. Preliminaries...........................................................................................4

4. Experimental study on fuzzy rule-based approach to

geographic classification of virgin olive oil using T-operators.13

5. Conclusion............................................................................................18

Acknowledgement.....................................................................................18

Chapter 2 Modelling Driving Forces of Urban Growth with Fuzzy Sets and GIS................................................................................................................23

Abstract.................................................................................................23

1. INTRODUCTION................................................................................24

2. Driving forces of urban growth.......................................................26

3. Fuzzy sets.............................................................................................33

4. Results and discussion.......................................................................37

5. Conclusions..........................................................................................58

Acknowledgements.............................................................................59

Chapter 3 A Fuzzy Belief-Desire-Intention Model for Agent-Based Image Analysis.......................................................................................................65

Abstract.................................................................................................65

1. Introduction..........................................................................................66

2. Agent-based and multiagent systems.............................................67

3. A fuzzy believe-desire-intention model for agent-based

image analysis......................................................................................71

4. Conclusion............................................................................................78

5. Outlook..................................................................................................79

Chapter 4 A Hybrid of Fuzzy and Fuzzy Self-Tuning PID Controller for

Servo Electro-Hydraulic System ..........................................................83

1. Introduction..........................................................................................83

2. Servo electro-hydraulic system .......................................................84

3. System descriptions ...........................................................................86

4. Controller designs .............................................................................87

5. The experimental resultS...................................................................95

6. Conclusions .........................................................................................98

Acknowledgement...............................................................................98

Chapter 5 A Concise Fuzzy Rule Base to Reason Student Performance Based

on Rough-Fuzzy Approach ..................................................................100

1. Introduction........................................................................................100

2. Student modeling and the learning criteria ...............................102

3. Human expert Fuzzy Inference System ......................................105

4. Development of Adaptive Neuro-Fuzzy Inference System (ANFIS) .109

5. Rough-fuzzy approach ...................................................................116

6. Conclusion..........................................................................................121

7. Acknowledgment .............................................................................122

Chapter 6 A Fuzzy Approach for Risk Analysis with Application in Project

Management ...........................................................................................125

1. Introduction ......................................................................................125

2. Classic and fuzzy risk analysis .....................................................127

3. Fuzzy model .....................................................................................130

4. Multi critical PERT by considering risky levels.........................133

5. Rescue robot path planning ..........................................................136

6. Conclusion .........................................................................................147

Chapter 7 Standard Fuzzy Sets and some Many-Valued Logics....................151

1. Introduction........................................................................................151

2. Zadeh’s theory of standard fuzzy sets.........................................153

3. On De Morgan algebras..................................................................155

4. Algebra of standard fuzzy sets......................................................158

5. Where is the hiding-place of fuzziness?......................................161

6. Common features of many-valued logics based on Zadeh

algebra.................................................................................................162

7. Description of Kleene’s logic..........................................................166

8. On Łukasiewicz’ many-valued logic.............................................169

9. The relationship between Łukasiewicz logic and

MV-algebras.......................................................................................174

10. Conclusion..........................................................................................176

Chapter 8 A Mamdani Type Fuzzy Logic Controller........................................179

1. Introduction........................................................................................179

2. Preliminaries.......................................................................................181

3. Standard fuzzy logic controllers....................................................185

4. Mamdani FLC with different inputs and implications.............194

5. Applications.......................................................................................198

6. Conclusion..........................................................................................206

Chapter 9 A Fuzzy Logic Approach for Remote Healthcare Monitoring by Learning and Recognizing Human Activities of Daily Living ..209

1. Introduction........................................................................................209

2. CompanionAble project ..................................................................210

4. The multimodal telemonitoring platform....................................216

5. Fuzzy logic activities recognition approach ...............................221

6. DSS integration system ..................................................................224

7. Experimentation and results .........................................................232

8. Conclusion .........................................................................................232

9. Acknowledgments ...........................................................................233

Chapter 10 A Clinical Application of Fuzzy Logic ............................................236

1. Introduction........................................................................................236

2. Development of fuzzy correlation model ...................................240

3. Operation of fuzzy correlation model..........................................246

4. Conclusion..........................................................................................250

5. Acknowledgment..............................................................................251

Chapter 11 A Fuzzy Finite Element Method Programmed in MATLAB for the Analysis of Uncertain Control Systems of Structures...................255

1. Introduction........................................................................................255

2. Dynamic analysis and control of structures................................257

3. Uncertainty and fuzzy arithmetic..................................................260

4. Fuzzy Finite Element procedure in MATLAB............................263

5. A case study of uncertainty propagation....................................267

6. Conclusion..........................................................................................271

7. Acknowledgment..............................................................................272

Citation......................................................................................................275

Index...........................................................................................................277

About Author

Peter Elliott obtained his Ph.D. Degree in Mechanical Engineering from Technological University, Saskatchewan. He is a Guest Lecturer at University College, Tabasco. He has written over 50 journal, conference papers, articles and research papers on robotic system, fuzzy logic, vision system, and industrial robotics. His interest research areas are software engineering, computer engineering, and robotics. Elliott has also won a "University Excellence in Teaching" award for his outstanding contribution towards the researcher community especially in the higher education programs.