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Handbook of Research on Computational Intelligence for Engineering, Science, and Business

Book Description

Using the same strategy for the needs of image processing and pattern recognition, scientists and researchers have turned to computational intelligence for better research throughputs and end results applied towards engineering, science, business and financial applications. Handbook of Research on Computational Intelligence for Engineering, Science, and Business discusses the computation intelligence approaches, initiatives and applications in the engineering, science and business fields. This reference aims to highlight computational intelligence as no longer limited to computing-related disciplines and can be applied to any effort which handles complex and meaningful information.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Dedication
  6. Preface
  7. Acknowledgment
  8. Section 1: Overview of Computational Intelligence
    1. Chapter 1: Computational Intelligence Using Type-2 Fuzzy Logic Framework
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. TYPE-2 FUZZY SYSTEMS
      5. 4. HYBRID TYPE-2 FUZZY LOGIC SYSTEM
      6. 5. AN EVALUATION OF MULTIPLE ATTRIBUTES DECISION MAKING BASED ON RANKING VALUES OF STUDENTS’ PERFORMANCE IN ORAL PRESENTATION USING INTERVAL TYPE-2 FUZZY APPROACH
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
      9. APPENDIX: EXTERNAL LINKS
    2. Chapter 2: Soft Computing Based Statistical Time Series Analysis, Characterization of Chaos Theory, and Theory of Fractals
      1. ABSTRACT
      2. INTRODUCTION
      3. SOFT-COMPUTING BASED STUDY IN PREDICTION
      4. SOFT-COMPUTING BASED STUDY IN DATA COMPRESSION
      5. SOFT-COMPUTING BASED STUDY IN EXPLANATORY ANALYSIS
      6. SOFT-COMPUTING BASED STUDY IN SIGNAL PROCESSING
      7. SOFT-COMPUTING BASED STUDY IN CHARACTERIZATION OF CHAOS THEORY
      8. SOFT-COMPUTING BASED STUDY IN THEORY OF FRACTALS
      9. CONCLUSION
    3. Chapter 3: Machine Intelligence Using Hierarchical Memory Networks
      1. ABSTRACT
      2. INTRODUCTION
      3. NETWORKS IN INFORMATION PROCESSING
      4. MEMORY NETWORK CELL AND ARCHITECTURE
      5. CHARACTER RECOGNITION UNDER RANDOM DEFORMATIONS
      6. CONCLUDING REMARKS
  9. Section 2: Image Processing and Segmentation
    1. Chapter 4: Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SECTION 1: INFORMATION THEORETICAL REGION MERGING APPROACHES
      5. SECTION 2: COOPERATIVE FUSION OF HIERARCHICAL SEGMENTATION RESULTS
      6. FUTURE GUIDELINES
      7. CONCLUSION
    2. Chapter 5: Multilevel Image Segmentation by a Multiobjective Genetic Algorithm Based OptiMUSIG Activation Function
      1. ABSTRACT
      2. INTRODUCTION
      3. THE SEGMENTATION PROBLEM
      4. THE SURVEY OF IMAGE SEGMENTATION
      5. MULTIOBJECTIVE OPTIMIZATION
      6. MULTI LAYER SELF ORGANIZING NEURAL NETWORK (MLSONN) ARCHITECTURE
      7. OPTIMIZED MULTILEVEL SIGMOIDAL (OPTIMUSIG) ACTIVATION FUNCTION
      8. PARALLEL OPTIMIZED MULTILEVEL SIGMOIDAL (PARAOPTIMUSIG) ACTIVATION FUNCTION
      9. POPULAR IMAGE SEGMENTATION QUALITY EVALUATION METRICS
      10. PROPOSED METHODOLOGY
      11. RESULTS
      12. QUANTITATIVE PERFORMANCE ANALYSIS OF SEGMENTATION
      13. IMAGE SEGMENTATION OUTPUTS
      14. CONCLUSION
    3. Chapter 6: A Novel Fuzzy Rule Guided Intelligent Technique for Gray Image Extraction and Segmentation
      1. ABSTRACT
      2. INTRODUCTION
      3. SURVEY
      4. PROPOSED WORK
      5. RESULTS AND ANALYSIS
      6. CONCLUSION
    4. Chapter 7: Graph Based Segmentation of Digital Images
      1. ABSTRACT
      2. INTRODUCTION
      3. SEGMENTATION PROBLEM
      4. MOTIVATION
      5. GRAPH APPROACHES
      6. CONCLUSION
    5. Chapter 8: Development of a Stop-Line Violation Detection System for Indian Vehicles
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. CREATION OF IMAGE DATASET
      5. PRESENT WORK
      6. RESULTS AND DISCUSSION
      7. CONCLUSION
    6. Chapter 9: A Comparative Study of Unsupervised Video Shot Boundary Detection Techniques Using Probabilistic Fuzzy Entropy Measures
      1. ABSTRACT
      2. INTRODUCTION
      3. RECENT SOFT COMPUTING TRENDS IN VIDEO SHOT DETECTION TECHNIQUES
      4. CHAPTER DELIVERABLE
      5. PROPOSED METHODOLOGY
      6. RESULTS
      7. CONCLUSION
    7. Chapter 10: A Hierarchical Multilevel Image Thresholding Method Based on the Maximum Fuzzy Entropy Principle
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. A HIERARCHICAL MULTILEVEL IMAGE THRESHOLDING METHOD BASED ON THE MAXIMUM FUZZY ENTROPY PRINCIPLE
      5. 4. APPLICATION IN CONTENT-BASED IMAGE RETRIEVAL
      6. 5. FUTURE RESEARCH DIRECTIONS
      7. 6. CONCLUSION
    8. Chapter 11: Adaptive Median Filtering Based on Unsupervised Classification of Pixels
      1. ABSTRACT
      2. INTRODUCTION
      3. NOISE MODEL
      4. FUTURE RESEARCH DIRECTIONS AND CONCLUSION
  10. Section 3: Database Oriented Techniques
    1. Chapter 12: Data Clustering Algorithms Using Rough Sets
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. INTRODUCTION TO ROUGH SET THEORY AND DEFINITIONS
      5. THE ALGORITHMS
      6. COMPARISONS OF MMR, MMeR, AND SDR
      7. EMPERICAL ANALYSIS
      8. FUTURE RESEARCH DIRECTIONS
      9. CONCLUSION
    2. Chapter 13: Evolution of Genetic Algorithms in Classification Rule Mining
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. DEFINITIONS
      5. MAIN FOCUS OF THE CHAPTER
      6. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    3. Chapter 14: Database Anonymization Techniques with Focus on Uncertainty and Multi-Sensitive Attributes
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE SURVEY
      4. CURRENT STATUS AND CHAPTER ORGANISATION
      5. PROBLEMS IN K-ANONYMITY
      6. EXAMPLE DATABASE TABLE
      7. SINGLE SENSITIVE ATTRIBUTE L-DIVERSITY ALGORITHMS
      8. WORKING OF THE ALGORITHM
      9. ALGORITHMS TO ANONYMIZE IMPRECISE DATA TABLES
      10. PROBLEMS FOR FURTHER STUDY
      11. CONCLUSION
    4. Chapter 15: Using Data Masking for Balancing Security and Performance in Data Warehousing
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND RELATED WORK
      4. MOBAT: A MODULUS-BASED DATA MASKING TECHNIQUE FOR BALANCING SECURITY AND PERFORMANCE IN DATA WAREHOUSES
      5. EXPERIMENTAL EVALUATION
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    5. Chapter 16: Schedulers Based on Ant Colony Optimization for Parameter Sweep Experiments in Distributed Environments
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. Swarm intelligence
      5. RELATED WORK OF JOB SCHEDULING BASED ON ACO
      6. ANALYSIS OF ACO-BASED SCHEDULING APPROACHES
      7. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
  11. Section 4: Classification, Design, and Modeling
    1. Chapter 17: Particle Swarm Optimization Algorithm and its Hybrid Variants for Feature Subset Selection
      1. ABSTRACT
      2. INTRODUCTION
      3. BIO-INSPIRED COMPUTATION FOR FEATURE SUBSET SELECTION
      4. PARTICLE SWARM OPTIMIZATION
      5. PROPOSED BPSO BASED ALGORITHMS FOR FEATURE SELECTION
      6. SIMULATION EXPERIMENTS AND RESULTS
      7. CONCLUSION
    2. Chapter 18: An Evolving System in the Text Classification Problem
      1. ABSTRACT
      2. INTRODUCTION
      3. THE PROBLEM
      4. BACKGROUND TECHNIQUES
      5. EXPECTATION MAXIMIZATION AND GAUSSIAN MIXTURE MODEL
      6. ARTIFICIAL NEURAL NETWORKS
      7. EVOLVING PROBABILISTIC NEURAL NETWORK (EPNN)
      8. THE COMPARED TECHNIQUES
      9. EXPERIMENTS
      10. FUTURE RESEARCH DIRECTIONS
      11. CONCLUSION
    3. Chapter 19: Fuzzy Based Modeling, Control, and Fault Diagnosis of Permanent Magnet Synchronous Generator
      1. ABSTRACT
      2. INTRODUCTION
      3. MATHEMATICAL MODELING OF PMSG
      4. T-S FUZZY MODEL
      5. FUZZY LOGIC CONTROLLER
      6. FAULT SIMULATION OF PMSG
      7. FUZZY BASED FAULT DETECTION
      8. CONCLUSION AND FUTURE DIRECTIONS
      9. APPENDIX 1
      10. APPENDIX 2
    4. Chapter 20: Algorithms and Principles for Intelligent Design of Flapping Wing Micro Aerial Vehicles
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND LITERATURE SURVEY
      4. ANALYTICAL DEVELOPMENT
      5. NUMERICAL IMPLEMENTATION OF MAV DESIGN SOFTWARE FOR VARIOUS PLATFORMS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    5. Chapter 21: Fuzzy-Controlled Energy-Conservation Technique (FET) for Mobile ad hoc Networks
      1. ABSTRACT
      2. INTRODUCTION
      3. OVERVIEW OF NAP-REQUEST AND NAP-REPLY
      4. INPUT PARAMETERS OF NAP-REQUEST
      5. RULE BASES OF NAP-REQUEST
      6. INPUT PARAMETERS OF NAP-ALLOW
      7. CONCLUSION
    6. Chapter 22: Decision Fusion of Multisensor Images for Human Face Identification in Information Security
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORKS
      4. SYSTEM OVERVIEW
      5. GRADIENT BASED FUSION OF WAVELET COEFFICIENTS OF IR AND VISUAL IMAGES
      6. CANDID CO-VARIANCE FREE INCREMENTAL PCA
      7. CLASSIFICATION USING SUPPORT VECTOR MACHINE
      8. DECISION FUSION
      9. RECEIVER OPERATING CHARACTERISTICS CURVE
      10. EXPERIMENTS
      11. EXPERIMENTAL RESULTS AND DISCUSSION
      12. COMPARATIVE STUDY
      13. CONCLUSION AND FUTURE WORKS
    7. Chapter 23: Modernization of Healthcare and Medical Diagnosis System Using Multi Agent System (MAS)
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. APPLICATIONS OF TELEMEDICINE
      5. PROS AND CONS OF TELEMEDICINE
      6. MULTI AGENT SYSTEM BASED APPLICATION OVER TELEMEDICINE SYSTEMS
      7. MULTI AGENT SYSTEM IN MEDICAL PARADIGM
      8. APPLICATION OF MAS IN MEDICAL SCENARIO
      9. A NEW SCHEME FOR MEDICAL DIAGNOSIS BASED ON MAS
      10. CONCLUSION
  12. Section 5: Applications
    1. Chapter 24: Watermarking of Data Using Biometrics
      1. ABSTRACT
      2. INTRODUCTION
      3. WATERMARKING
      4. BIOMETRICS
      5. WATERMARKING WITH BIOMETRICS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    2. Chapter 25: Quantum Backpropagation Neural Network Approach for Modeling of Phenol Adsorption from Aqueous Solution by Orange Peel Ash
      1. ABSTRACT
      2. INTRODUCTION
      3. REMOVAL OF PHENOL BY VARYING DIFFERENT OPERATIONAL FACTORS
      4. COMPARISON OF EXPERIMENTAL DATA AND NETWORK OUTPUT BY GRAPH
      5. QUANTUM COMPUTING
      6. COMPARISON OF EXPERIMENTAL DATA AND NETWORK OUTPUT BY GRAPH
      7. CONCLUSION
    3. Chapter 26: Computational Intelligence for Pathological Issues in Precision Agriculture
      1. ABSTRACT
      2. INTRODUCTION
      3. PREVIOUS RESEARCH WORK
      4. TECHNOLOGIES USED IN THIS CHAPTER
      5. MATLAB OVERVIEW
      6. SYSTEM DESIGN
      7. IMPLEMENTATION
      8. CASE STUDY 1
      9. CASE STUDY 2
      10. FUTURE RESEARCH DIRECTIONS
      11. CONCLUSION
    4. Chapter 27: Cancer Gene Expression Data Analysis Using Rough Based Symmetrical Clustering
      1. ABSTRACT
      2. INTRODUCTION
      3. EXISTING WORKS
      4. ROUGH SETS THEORY
      5. SYMMETRY BASED CLUSTERING
      6. EXPERIMENTAL FRAMEWORK
      7. PERFORMANCE ANALYSIS
      8. TEST FOR STATISTICAL SIGNIFICANCE
      9. CONCLUSION
    5. Chapter 28: Computer Intelligence in Healthcare
      1. ABSTRACT
      2. INTRODUCTION
      3. ADAPTIVE INTELLIGENT CONTROLLER FOR COOLING SYSTEMS
      4. INTELLIGENT DEVICE TO RECOGNIZE DIFFERENT WBC FROM MICROSCOPIC IMAGES
      5. FUTURE PLAN
    6. Chapter 29: Intelligence in Web Technology
      1. ABSTRACT
      2. INTRODUCTION
      3. WEB TECHNOLOGY EVOLUTION
      4. TERMINOLOGY AND THEIR MEANING
      5. SOFTWARE ENGINEERING ISSUES
      6. APPLICATION AREAS CAN BE BENEFITED
      7. SURVEY OF LITERATURES FROM SEMANTIC WEB CONFERENCE
      8. CONCLUSION AND THE ROAD AHEAD
      9. DEDICATION
    7. Chapter 30: Performance Comparison of Different Intelligent Techniques Applied on Detecting Proportion of Different Component in Manhole Gas Mixture
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MANHOLE GAS MIXTURE
      5. OVERVIEW OF THE RECOGNITION SYSTEM
      6. INTELLIGENT TECHNIQUES
      7. PERFORMANCE COMPARISION
      8. FUTURE RESEARCH DIRECTIONS
      9. CONCLUSION
  13. Compilation of References
  14. About the Contributors