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Handbook of Research on Artificial Intelligence Techniques and Algorithms

Book Description

For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Foreword
  7. Foreword
  8. Foreword
  9. Foreword
  10. Foreword
  11. Foreword
  12. Preface
  13. Acknowledgment
  14. Chapter 1: Robust Control and Synchronization of Chaotic Systems with Actuator Constraints
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. PROBLEM STATEMENT
    5. 4. THE APPROACH PROPOSED
    6. 5. SIMULATION RESULTS
    7. 6. DISCUSSION
    8. 7. FUTURE RESEARCH DIRECTIONS
    9. 8. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. APPENDIX
  15. Chapter 2: An Intelligent Process Development Using Fusion of Genetic Algorithm with Fuzzy Logic
    1. ABSTRACT
    2. INTRODUCTION
    3. CLASSIFICATION OF COMPUTATIONAL APPROACHES
    4. THE ROLE OF SOFT COMPUTING FOR DESIGNING INTELLIGENT SYSTEM
    5. EVOLUTIONARY COMPUTING IN SEARCH AND OPTIMIZATION
    6. EVOLUTIONARY ALGORITHMS
    7. BASIC STEPS OF EVOLUTION CYCLE
    8. COMPARISON OF CLASSICAL OPTIMIZATION METHODS VS. GENETIC ALGORITHMS
    9. GENETIC ALGORITHM-A PRIME TYPE OF EA
    10. TYPES OF APPLICATIONS DEVELOPED USING GENETIC ALGORITHM
    11. WEAKNESS OF GENETIC ALGORITHM
    12. LINGUISTIC KNOWLEDGE REPRESENTATION WITH FUZZY LOGIC
    13. DIFFERENCE BETWEEN BOOLEAN LOGIC AND FUZZY LOGIC
    14. MEMBERSHIP FUNCTIONS
    15. FUZZY LOGIC BASED SYSTEMS
    16. FUZZY RULE BASED SYSTEM
    17. APPLICATION OF HEART DISEASE DIAGNOSIS
    18. DEVELOPMENT OF INTELLIGENT PROCESS FOR DIAGNOSIS OF HEART DISEASE
    19. RESULTS AND DISCUSSION
    20. SIMILAR KIND OF APPLICATIONS
    21. CONCLUSION
    22. REFERENCES
    23. ADDITIONAL READING
    24. KEY TERMS AND DEFINITIONS
    25. APPENDIX
  16. Chapter 3: A Stochastic Approach to Product-Driven Supply Chain Design
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. THE PRODUCT TYPES, PRODUCT LIFE CYCLE, AND SUPPLY CHAIN STRATEGIES
    5. STATE OF THE ART
    6. MAIN FOCUS OF THE CHAPTER
    7. PHASE I: A MULTI-CRITERIA DECISION MAKING PROBLEM
    8. PHASE II: THE SUPPLY CHAIN NETWORK DESIGN UNDER PRODUCT LIFE CYCLE UNCERTAINTY
    9. THE MODEL
    10. EXPERIMENTAL RESULTS
    11. SENSITIVITY ANALYSIS
    12. RESULTS’ INTERPRETATION
    13. FUTURE RESEARCH DIRECTIONS
    14. CONCLUSION
    15. REFERENCES
    16. ADDITIONAL READING
    17. KEY TERMS AND DEFINITIONS
    18. APPENDIX
  17. Chapter 4: The Bees Algorithm and Its Applications
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. 1. BEES IN NATURE
    5. 2. THE BEES ALGORITHM
    6. 3. THE ENHANCEMENT TO THE BEES ALGORITHM
    7. 4. THE APPLICATIONS OF THE BEES ALGORITHM
    8. 5. FUTURE RESEARCH DIRECTIONS
    9. 6. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. APPENDIX
  18. Chapter 5: Optimum Allocation of Transmission Technologies for Solving the BTS Interconnection Problem in Cellular Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. METHODOLOGY
    4. CASE STUDY
    5. DISCUSSION
    6. CONCLUSION
    7. FUTURE RESEARCH
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
    11. APPENDIX
  19. Chapter 6: Machine Learning Approaches to Automated Medical Decision Support Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND: CLASSIFICATION
    4. SELF-ORGANIZING MAP
    5. METHODS
    6. RESULTS
    7. FUTURE WORK
    8. CONCLUSION
    9. ACKNOWLEDGMENT
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  20. Chapter 7: Application of Soft Computing Techniques for Renewable Energy Network Design and Optimization
    1. ABSTRACT
    2. INTRODUCTION
    3. SOFT COMPUTING TECHNIQUES
    4. APPLICATION OF SPATIAL AND TEMPORAL ANALYSIS FOR RISK ASSESSMENT, OPTIMIZATION AND DECISION MAKING ON ENERGY NETWORK OPERATION
    5. APPLICATION DEMONSTRATION
    6. CONCLUDING REMARKS
    7. DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
  21. Chapter 8: Robust Fuzzy Digital PID Controller Design
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. IDENTIFICATION OF TS FUZZY MODEL BASED ON CLUSTERING ALGORITHM
    5. STRATEGY FOR ROBUST FUZZY DIGITAL PID CONTROLLER DESIGN
    6. EXPERIMENTAL RESULTS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
  22. Chapter 9: Comparison of Uncertainties in Membership Function of Adaptive Lyapunov NeuroFuzzy-2 for Damping Power Oscillations
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. ARTIFICIAL INTELLIGENCE
    5. ARTIFICIAL NEURAL NETWORK
    6. FUZZY LOGIC SYSTEM
    7. FUZZY SET THEORY
    8. FUZZY SET OPERATION
    9. TYPES OF FUZZY LOGIC SYSTEM
    10. NEUROFUZZY SYSTEMS
    11. POWER SYSTEM MODELING
    12. OPERATION, MODELING, AND CONTROL OF STATCOM
    13. CONTROL PROBLEM
    14. PROPOSED ADAPTIVE NEURO FUZZY TYPE-2 BASED SDC
    15. UPDATE PARAMETER RULES
    16. SIMULATION SETUP AND COMPARATIVE RESULTS
    17. CONCLUSION
    18. FUTURE RESEARCH DIRECTIONS
    19. REFERENCES
    20. ADDITIONAL READING
    21. KEY TERMS AND DEFINITIONS
    22. APPENDIX
  23. Chapter 10: New Neural Buildings Stereo Matching Method Applied to Very High Resolution Ikonos Images
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. STEREO MATCHING OF VERY HIGH RESOLUTION SATELLITE IMAGES
    5. PROPOSED SOLUTIONS AND RECOMMENDATIONS
    6. CONCLUSION
    7. FUTURE RESEARCH DIRECTIONS
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
  24. Chapter 11: Application of Fuzzy Logic for Mapping the Agro-Ecological Zones
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MAPPING THE AGROECOLOGICAL ZONES USING FUZZY LOGIC
    5. DISCUSSION
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
  25. Chapter 12: Fuzzy Integral-Based Kernel Regression Ensemble and Its Application
    1. ABSTRACT
    2. INTRODUCTION
    3. FUZZY MEASURE AND INTEGRAL
    4. PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHMS
    5. KERNEL REGRESSION ENSEMBLE BASED ON FUZZY INTEGRAL-KREFI
    6. KREFI
    7. EXPERIMENTS
    8. DISCUSSIONS
    9. FUTURE RESEARCH DIRECTIONS
    10. CONCLUSION
    11. ACKNOWLEDGMENT
    12. REFERENCES
    13. ADDITIONAL READING
    14. KEY TERMS AND DEFINITIONS
    15. APPENDIX
  26. Chapter 13: A Memetic Algorithm for the Multi-Depot Vehicle Routing Problem with Limited Stocks
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH LIMITED STOCKS
    5. DISCUSSION
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
    12. APPENDIX 1
  27. Chapter 14: Application of Artificial Intelligence Techniques to Handle the Uncertainty in the Chemical Process for Environmental Protection
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. FUZZY LOGIC SYSTEM
    5. GENETIC ALGORITHMS
    6. ANT COLONY OPTIMIZATION
    7. PARTICLE SWARM OPTIMIZATION
    8. ARTIFICIAL IMMUNE SYSTEM
    9. CULTURE ALGORITHM
    10. MOTIVATION
    11. DATA SOURCE
    12. PROBLEM STATEMENT
    13. GENERAL METHODOLOGY
    14. CASE STUDY
    15. CONCLUSION
    16. FUTURE RESEARCH WORK
    17. REFERENCES
    18. ADDITIONAL READING
    19. KEY TERMS AND DEFINITIONS
  28. Chapter 15: Combined Electromagnetism-Like Algorithm with Tabu Search to Scheduling
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. METHODOLOGY
    5. 4. EXPERIMENTAL DESIGN
    6. 5. CONCLUSION
    7. 6. FUTURE WORK
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
    11. APPENDIX
  29. Chapter 16: Cancer Biomarker Assessment Using Evolutionary Rough Multi-Objective Optimization Algorithm
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. ARCHIVED MULTI-OBJECTIVE SIMULATED ANNEALING: AMOSA
    5. ROUGH SETS THEORY
    6. PROPOSED EVOLUTIONARY ROUGH MULTI-OBJECTIVE OPTIMIZATION APPROACH
    7. PERFORMANCE ANALYSIS
    8. RESULTS
    9. DISCUSSION
    10. FUTURE RESEARCH DIRECTIONS
    11. CONCLUSION
    12. REFERENCES
    13. ADDITIONAL READING
    14. KEY TERMS AND DEFINITIONS
  30. Chapter 17: Application of Standard Deviation Method Integrated PSO Approach in Optimization of Manufacturing Process Parameters
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PARTICLE SWARM OPTIMIZATION
    5. PROPOSED APPROACH
    6. CASE STUDY
    7. DISCUSSION
    8. CONCLUSION
    9. FUTURE RESEARCH DIRECTIONS
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. APPENDIX
  31. Chapter 18: A Comparison for Optimal Allocation of a Reliability Algorithms Production System
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FORMULATION OF REDUNDANCY OPTIMIZATION PROBLEM
    4. 3. RELIABILITY ESTIMATION BASED ON USHAKOV’S TECHNIQUE
    5. 4. THE PSO OPTIMIZATION APPROACH
    6. 5. THE HARMONY SEARCH OPTIMIZATION APPROACH
    7. 6. THE IMMUNE SYSTEM OPTIMIZATION APPROACH
    8. 7. POWER DESIGN EXAMPLE
    9. 8. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  32. Chapter 19: From Optimization to Clustering
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PSO FOR OPTIMIZATION
    5. PSO FOR CLUSTERING
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
  33. Chapter 20: A Hybrid GA-GSA Algorithm for Optimizing the Performance of an Industrial System by Utilizing Uncertain Data
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. NOTATIONS
    4. 3. BASIC CONCEPTS ON INTUITIONISTIC FUZZY SET (IFS)
    5. 4. RAM PARAMETERS
    6. 5. METHODOLOGY
    7. 6. CASE STUDY
    8. 7. COMPUTATIONAL RESULTS
    9. 8. CONCLUSION
    10. 9. FUTURE RESEARCH DIRECTIONS
    11. ACKNOWLEDGMENT
    12. REFERENCES
    13. ADDITIONAL READING
    14. KEY TERMS AND DEFINITIONS
  34. Chapter 21: Robust Vehicle Routing Solutions to Manage Time Windows in the Case of Uncertain Travel Times
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND ON ROBUSTNESS
    4. METHODOLOGY OF THE RESEARCH
    5. RESULTS
    6. DISCUSSION
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
  35. Chapter 22: Fuzzy Logic in Healthcare
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND: FUZZY LOGIC BASICS
    4. FUZZY LOGIC IN THE MEDICAL DOMAIN
    5. FUTURE RESEARCH DIRECTIONS
    6. DISCUSSION
    7. CONCLUSION
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
  36. Chapter 23: A Metaheuristic Algorithm for OCR Baseline Detection of Arabic Languages
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PROBLEMS OF THE CONVENTIONAL METHODS
    5. SOLUTIONS AND RECOMMENDATIONS
    6. EXPERIMENTS
    7. RESULTS
    8. SOLUTIONS PROCEDURES
    9. DISCUSSION
    10. FUTURE RESEARCH DIRECTIONS
    11. CONCLUSION
    12. REFERENCES
    13. ADDITIONAL READING
    14. KEY TERMS AND DEFINITIONS
  37. Chapter 24: GPR and RVM-Based Predictions of Surface and Hole Quality in Drilling of AISI D2 Cold Work Tool Steel
    1. ABSTRACT
    2. INTRODUCTION
    3. METHODOLOGY
    4. DETAILS OF RVM
    5. DETAILS OF GPR
    6. RESULTS AND DISCUSSION
    7. CONCLUSION
    8. FUTURE RESEARCH
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
    12. APPENDIX A
    13. APPENDIX B
  38. Chapter 25: Early Warning System Framework Proposal Based on Structured Analytical Techniques, SNA, and Fuzzy Expert System for Different Industries
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. STRUCTURED ANALYTICAL TECHNIQUES AND SNA ANALYSIS IN EWS DEVELOPMENT
    5. 4. EARLY WARNING SYSTEM FRAMEWORK PROPOSAL BASED ON STRUCTURED ANALYTICAL TECHNIQUES, SNA AND FUZZY EXPERT SYSTEM
    6. 5. FUTURE RESEARCH
    7. 6. CONCLUSION
    8. REFERENCES
    9. ADDITIONAL READING
    10. KEY TERMS AND DEFINITIONS
    11. ENDNOTES
  39. Compilation of References
  40. About the Contributors