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Handbook of Research on Novel Soft Computing Intelligent Algorithms

Book Description

As technologies grow more complex, modeling and simulation of new intelligent systems becomes increasingly challenging and nuanced; specifically in diverse fields such as medicine, engineering, and computer science. Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications explores emerging technologies and best practices to effectively address concerns inherent in properly optimizing advanced systems. With applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies, this exceptional reference will serve as an important tool for decision makers, managers, researchers, economists, and industrialists across a wide range of scientific fields.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Foreword
  7. Foreword
  8. Foreword
  9. Preface
    1. CHAPTER 1
    2. CHAPTER 2
    3. CHAPTER 3
    4. CHAPTER 4
    5. CHAPTER 5
    6. CHAPTER 6
    7. CHAPTER 7
    8. CHAPTER 8
    9. CHAPTER 9
    10. CHAPTER 10
    11. CHAPTER 11
    12. CHAPTER 12
    13. CHAPTER 13
    14. CHAPTER 14
    15. CHAPTER 15
    16. CHAPTER 16
    17. CHAPTER 17
    18. CHAPTER 18
    19. CHAPTER 19
    20. CHAPTER 20
    21. CHAPTER 21
    22. CHAPTER 22
    23. CHAPTER 23
    24. CHAPTER 24
    25. CHAPTER 25
    26. CHAPTER 26
    27. CHAPTER 27
    28. CHAPTER 28
    29. CHAPTER 29
    30. CHAPTER 30
    31. CHAPTER 31
    32. CHAPTER 32
  10. Acknowledgment
  11. Chapter 1: Customer Relationship Management and Data Mining
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. DATA AND METHODOLOGY
    5. DISCUSSIONS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. NOMENCLATURE
  12. Chapter 2: Hybrid Optimization Techniques for Industrial Production Planning
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PRODUCTION PLANNING PROBLEMS
    5. IMPLEMENTATION OF METHODS AND RECOMMENDATIONS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. APPENDIX
  13. Chapter 3: Chaotic Systems and Their Recent Implementations on Improving Intelligent Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. FOUNDATIONS
    4. IMPROVING INTELLIGENT SYSTEMS VIA CHAOTIC SYSTEMS
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
  14. Chapter 4: Supply Chain Design Including Quality Considerations
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. QUALITY COST MODEL FOR SUPPLY CHAIN DESIGN
    5. 4. SOLUTION METHODS BASED ON METAHEURISTICS
    6. 5. EXPERIMENTAL STUDY
    7. 6. COMPUTATIONAL RESULTS
    8. 7. FUTURE RESEARCH DIRECTIONS
    9. 8. CONCLUSION
    10. APPENDIX 1
    11. APPENDIX 2
  15. Chapter 5: Power Management in Microgrids
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MULTI-AGENT SYSTEMS
    5. PETRI NETS
    6. MODELING AND SIMULATION
    7. RESULTS AND DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
  16. Chapter 6: Metaheuristics Methods for Configuration of Assembly Lines
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. CRITICAL REVIEW ON THE RELATED WORK
    5. ASSEMBLY LINES MODEL
    6. METAHEURISTICS METHOD IN ASSEMBLY LINES
    7. DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. APPENDIX
  17. Chapter 7: Population-Based vs. Single Point Search Meta-Heuristics for a PID Controller Tuning
    1. ABSTRACT
    2. INTRODUCTION
    3. META-HEURISTICS BACKGROUND
    4. APPLICATION OF META-HEURISTICS FOR A PID CONTROLLER TUNING
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
    7. APPENDIX 1
    8. APPENDIX 2
  18. Chapter 8: Fuzzy System Dynamics
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. RELATED WORK
    5. FUZZY SYSTEM DYNAMICS PARADIGM
    6. FUZZIFICATION
    7. DEFUZZIFICATION
    8. FUZZY SYSTEM DYNAMICS MODEL DEVELOPMENT
    9. CAUSAL LOOP ANALYSIS
    10. FUZZY SYSTEM DYNAMICS MODEL
    11. ILLUSTRATIVE EXPERIMENTS
    12. RESULTS AND DISCUSSIONS
    13. CONCLUSIONS
    14. CONTRIBUTION TO THEORY
    15. MANAGERIAL IMPLICATIONS
    16. FUTURE RESEARCH DIRECTIONS
  19. Chapter 9: Genetic Algorithms for Small Enterprises Default Prediction
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. HYPOTHESES
    5. METHODOLOGY
    6. RESULTS
    7. DISCUSSION
    8. MANAGERIAL IMPLICATION
    9. FUTURE RESEARCH DIRECTIONS
    10. CONCLUSIONS
    11. APPENDIX
  20. Chapter 10: The Use of Soft Computing in Management
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. FUZZY LOGIC
    5. NEURAL NETWORKS
    6. EVOLUTIONARY ALGORITHMS
    7. DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
  21. Chapter 11: Genetic Algorithms Quality Assessment Implementing Intuitionistic Fuzzy Logic
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. GENETIC ALGORITHMS QUALITY ASSESSMENT APPLYING IFL
    5. DISCUSSION
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. APPENDIX
  22. Chapter 12: Melanocytic Lesions Screening through Particle Swarm Optimization
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND ON ALGEBRAIC FUNCTIONS OF VIEWS
    4. COMPARISON OF THE TWO IMAGES OF THE MOLE
    5. EXPERIMENTS AND RESULTS
    6. FUTURE RESEARCH DIRECTIONS
    7. DISCUSSION
    8. CONCLUSION
    9. APPENDIX
  23. Chapter 13: Quantification of Corporate Performance Using Fuzzy Analytic Network Process
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. LITERATURE REVIEW
    5. METHODOLOGY
    6. ANP BASED PERFORMANCE MEASUREMENT SYSTEM: E-COMMERCE CASE
    7. DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. APPENDIX
  24. Chapter 14: Predicting Uncertain Behavior and Performance Analysis of the Pulping System in a Paper Industry using PSO and Fuzzy Methodology
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BASIC ASPECTS OF FUZZY SET THEORY
    4. 3. SHORTCOMING OF THE EXISTING LITERATURE
    5. 4. EVOLUTIONARY TECHNIQUES: GA AND PSO
    6. 5. METHODOLOGY
    7. 6. AN ILLUSTRATIVE EXAMPLE
    8. CONCLUSION
    9. FUTURE RESEARCH DIRECTIONS
  25. Chapter 15: Multi-Objective Generation Scheduling Using Genetic-Based Fuzzy Mathematical Programming Technique
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND OF FUZZY SETS IN OPF
    4. GENETIC ALGORITHM IN FUZZY OPTIMAL POWER FLOW
    5. OPF PROBLEM STATEMENT
    6. FUZZY OPF PROBLEM
    7. FUZZY MULTI-OBJECTIVE OPF PROBLEM SOLUTION
    8. STUDY CASE
    9. DISCUSSION AND COMPARISON
    10. CONCLUSION
    11. FUTURE RESEARCH DIRECTIONS
    12. APPENDIX 1
    13. APPENDIX 2
  26. Chapter 16: Evaluation of Genetic Algorithm as Learning System in Rigid Space Interpretation
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. LITERATURE REVIEW
    5. STOCHASTIC APPROXIMATION PROCEDURE
    6. MATHEMATICAL MODEL OF LEARNING
    7. FUNDAMENTAL THEOREM OF GENETIC ALGORITHM
    8. DISCUSSION
    9. CONCLUSION
    10. FURTHER WORK
    11. CRITICAL ANALYSIS ON THE ADVANTAGES AND DISADVANTAGES
    12. APPENDIX
  27. Chapter 17: Data Mining Models as a Tool for Churn Reduction and Custom Product Development in Telecommunication Industries
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. VEZA COMPANY–GOALS OF THE PROJECT
    5. 4. PROPOSED SOLUTION FROM PERSPECTIVE OF DATA MINING METHODS
    6. 5. DATA FOUNDATION
    7. 6. MODELING SOLUTION FOR CALCULATION
    8. 7. CHURN PREDICTION MODELLING
    9. 8. REVEALED KNOWLEDGE AS A BASE FOR THE CHURN MITIGATION STRATEGIES AND THE NEW PRODUCTS DEVELOPMENT
    10. 9. DISCUSSION
    11. 10. FUTURE RESEARCH
    12. 11. CONCLUSION
    13. APPENDIX
  28. Chapter 18: Investigating the Efficiency of GRASP for the SDST HFS with Controllable Processing Times and Assignable Due Dates
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. LITERATURE REVIEW
    5. PROBLEM DESCRIPTION
    6. GRASP AND SA INTRODUCTION AND TUNING
    7. COMPUTATIONAL RESULTS
    8. DISCUSSION
    9. FUTURE RESEARCH DIRECTIONS
    10. CONCLUSION
  29. Chapter 19: Three Scenarios in Microgrid to Solve Management Problem for Residential Application Using Genetic Algorithms
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. GENETIC ALGORITHMS
    5. OPTIMIZATION MODEL
    6. SOLUTIONS AND RECOMMENDATIONS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
  30. Chapter 20: An On-Line PSO-Based Fuzzy Logic Tuning Approach
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND AND LITERATURE REVIEW
    4. LITERATURE REVIEW
    5. MICROGRID TEST SYSTEM
    6. PROPOSED OPTIMAL CONTROL DESIGN
    7. SIMULATION RESULTS
    8. ROBUSTNESS AGAINST PARAMETERS VARIATION
    9. FUTURE RESEARCH DIRECTIONS
    10. DISCUSSION
    11. CONCLUSION
    12. APPENDIX
  31. Chapter 21: Online Adaptive Neuro-Fuzzy Based Full Car Suspension Control Strategy
    1. ABSTRACT
    2. INTRODUCTION
    3. VEHICLE MODEL
    4. SEMI-ACTIVE CAR SUSPENSION SYSTEM
    5. CONTROL PROBLEM
    6. ADAPTIVE PID CONTROLLER DESIGN
    7. ADAPTIVE MAMDANI FUZZY LOGIC (AMFL) STRUCTURE
    8. ADAPTIVE SLIDING MODE BASED NEURO-FUZZY STRATEGY
    9. SIMULATION RESULTS
    10. DISCUSSION
    11. CRITICAL ANALYSIS ON THE MAJOR ADVANTAGES AND THE MAJOR DISADVANTAGES
    12. CONCLUSION
    13. FUTURE RECOMMENDATIONS
    14. APPENDIX
  32. Chapter 22: Metamodel-Based Optimum Design Examples of Structures
    1. ABSTRACT
    2. INTRODUCTION
    3. KRIGING INTERPOLATION METHOD
    4. STRUCTURAL DESIGN EXAMPLES
    5. FUTURE RESEARCH DIRECTIONS
    6. CONCLUSION
  33. Chapter 23: Applications of Reinforcement Learning and Bayesian Networks Algorithms to the Load-Frequency Control Problem
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. INTELLIGENT VERSUS CONVENTIONAL LFC DESIGN
    5. SOLUTIONS AND RECOMMENDATIONS
    6. SOLUTIONS PROCEDURES
    7. DISCUSSIONS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. APPENDIX
  34. Chapter 24: Non Linear and Non Gaussian States and Parameters Estimation using Bayesian Methods-Comparatives Studies
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORKS
    4. PROBLEM FORMULATION
    5. SIMULATION RESULTS ANALYSIS
    6. GENERATION OF DYNAMIC DATA
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. Appendix
  35. Chapter 25: Multiscale Filtering and Applications to Chemical and Biological Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. DATA FILTERING
    4. MULTISCALE FILTERING OF BIOLOGICAL DATA
    5. MULTISCALE MODELING OF CHEMICAL PROCESSES
    6. DISCUSSION
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
  36. Chapter 26: Hybrid Adaptive NeuroFuzzy Bspline Based SSSC Damping Control Paradigm
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. POWER SYSTEM MODEL
    5. CONTROL PROBLEM
    6. CONTROL SYSTEM DESIGN
    7. TRANSIENT STABILITY SIMULATION
    8. SIMULATION RESULTS
    9. DISCUSSION
    10. FUTURE RESEARCH DIRECTIONS
    11. CONCLUSION
    12. APPENDIX 1
    13. APPENDIX 2
  37. Chapter 27: Modeling and Simulation of a Stand-Alone Hydrogen Photovoltaic Fuel Cell Hybrid System
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY AND MODELING STAGE
    5. DESIGN AND OPTIMIZATION SYSTEM
    6. METHODS OF DESIGN SIMULATED SYSTEMS
    7. CHOICE MODELS OF COMPONENTS
    8. ANALYSIS OF DYNAMIC BEHAVIOR OF EHS PV-FC
    9. CONCLUSION
    10. FUTURE RESEARCH DIRECTIONS
  38. Chapter 28: Distributed Learning Algorithm Applications to the Scheduling of Wireless Sensor Networks
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. SOLUTIONS AND RECOMMENDATIONS
    5. SOLUTION PROCEDURE
    6. DISCUSSIONS
    7. MAJOR ADVANTAGES AND DISADVANTAGES
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. APPENDIX 1
    11. APPENDIX 2
  39. Chapter 29: A Fuzzy Simulated Evolution Algorithm for Hard Problems
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. PROBLEM DISCRIPTION
    5. FUZZY SIMULATED EVOLUTION ALGORITHM
    6. COMPUTATIONAL TESTS AND RESULTS
    7. CONCLUSION
    8. FURTHER RESEARCH
  40. Chapter 30: Fuzzy System Dynamics of Manpower Systems
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. FUZZY SYSTEM DYNAMICS APPROACH
    5. ILLUSTRATIVE APPLICATIONS, RESULTS, AND DISCUSSIONS
    6. CONCLUDING REMARKS
  41. Chapter 31: Systems with Concentrating Solar Radiation
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. SOLAR ENERGY POTENTIAL IN SERBIA
    5. COMPARATIVE ANALYSIS OF DIFFERENT TYPES CONCENTRATING SOLAR COLLECTORS
    6. A REVIEW OF CONCENTRATING SOLAR POWER PLANTS IN THE WORLD
    7. EXAMPLES: A REVIEW
    8. A PROTOTYPE RECEIVER FOR MEDIUM TEMPERATURE CONVERSION OF SOLAR RADIATION TO HEAT
    9. MEASURING INSTALLATION
    10. RESULTS AND DISCUSSION
    11. NUMERICAL SIMULATION OF CONCENTRATING SOLAR COLLECTOR P2CC WITH A SMALL CONCENTRATING RATIO
    12. THE RESULTS OF NUMERICAL SIMULATIONS
    13. REVIEW OF SOFTWARE FOR SIMULATION AND OPTIMIZATION OF ENERGY SYSTEMS AND CONCENRATING SOLAR COLLECTORS
    14. DISCUSSION
    15. CONCLUSION
    16. FUTURE RESEARCH DIRECTIONS
    17. APPENDIX 1
    18. APPENDIX 2
  42. Chapter 32: Widely Applicable Multi-Variate Decision Support Model for Market Trend Analysis and Prediction with Case Study in Retail
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MODELING FOR MARKET TRENDS ANALYSIS AND PREDICTION
    5. MODEL DEFINITION AND CASE STUDY FROM TEXTILE RETAIL
    6. MODEL DEVELOPMENT PROCESS
    7. MODEL APPLIANCE AND SELECTED OUTCOMES
    8. MODEL ADVANTAGES AND DISADVANTAGES
    9. DISCUSSION
    10. FUTURE RESEARCH
    11. CONCLUSION
    12. APPENDIX
  43. Compilation of References
  44. About the Contributors