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Intelligent Techniques for Data Analysis in Diverse Settings

Book Description

Data analysis forms the basis of many forms of research ranging from the scientific to the governmental. With the advent of machine intelligence and neural networks, extracting, modeling, and approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Intelligent Techniques for Data Analysis in Diverse Settings addresses the specialized requirements of data analysis in a comprehensive way. This title contains a comprehensive overview of the most innovative recent approaches borne from intelligent techniques such as neural networks, rough sets, fuzzy sets, and metaheuristics. Combining new data analysis technologies, applications, emerging trends, and case studies, this publication reviews the intelligent, technological, and organizational aspects of the field. This book is ideally designed for IT professionals and students, data analysis specialists, healthcare providers, and policy makers.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board
  6. Foreword
  7. Preface
    1. ORGANIZATION OF THE BOOK
    2. REFERENCES
  8. Chapter 1: Unified Wavelet Transform Analysis Adapted to Different Biomedical Applications
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. RELATIVE WAVELET ENERGY
    4. 3. DISTANCE SIMILARITY MEASURES
    5. 4. SIMULATION RESULTS
    6. 5. DISCUSSIONS
    7. 6. CONCLUSION
    8. REFERENCES
    9. APPENDIX
  9. Chapter 2: Swarm Intelligence Approaches to Shelf Space Allocation Problem with Linear Profit Function
    1. ABSTRACT
    2. INTRODUCTION
    3. LITERATURE REVIEW
    4. MATHEMATICAL MODEL
    5. EXPERIMENTAL DESIGN AND RESULTS
    6. CONCLUSION
    7. REFERENCES
    8. KEY TERMS AND DEFINITIONS
  10. Chapter 3: A Genetic Algorithm-Based Multivariate Grey Model in Housing Demand Forecast in Turkey
    1. ABSTRACT
    2. INTRODUCTION
    3. METHODOLOGY
    4. APPLICATION
    5. CONCLUSION
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  11. Chapter 4: Image Mining
    1. ABSTRACT
    2. INTRODUCTION
    3. IMAGE MINING
    4. CONTENT BASED IMAGE RETRIEVAL
    5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  12. Chapter 5: Comparative Analysis of Statistical, Machine Learning, and Grey Methods for Short-Term Electricity Load Forecasting
    1. ABSTRACT
    2. INTRODUCTION
    3. LITERATURE REVIEW
    4. FORECASTING ALGORITHMS
    5. SHORT-TERM LOAD FORECASTING WITH PROPOSED ALGORITHMS
    6. CONCLUSION
    7. REFERENCES
    8. KEY TERMS AND DEFINITIONS
  13. Chapter 6: A Soft Computing Approach to Customer Segmentation
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. LITERATURE REVIEW
    4. 3. RESEARCH METHODOLOGY
    5. 4. RESULTS OF THE ANALYSES
    6. 5. CONCLUSION AND DISCUSSIONS
    7. 6. LIMITATIONS AND FUTURE WORK
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
    10. APPENDIX
  14. Chapter 7: Data Mining for Multicriteria Single Facility Location Problems
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PCA-RANK
    5. SVM-RANK
    6. SOLUTIONS AND RECOMMENDATIONS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  15. Chapter 8: Heuristic Optimization-Based Clustering Solution for Large Facility Location Problems
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. EXPERIMENTAL RESULTS
    5. CONCLUSION
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  16. Chapter 9: Review of Business Intelligence and Intelligent Systems in Healthcare Domain
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. SIMILAR WORK ON BUSINESS INTELLIGENCE AND INTELLIGENT SYSTEMS IN HEALTH CONTEXT
    4. 3. SEARCH METHODOLOGY
    5. 4. BUSINESS INTELLIGENCE AND INTELLIGENT SYSTEMS APPLICATIONS IN HEALTHCARE
    6. 5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    7. REFERENCES
    8. KEY TERMS AND DEFINITIONS
  17. Chapter 10: Use of Chaotic Randomness Numbers
    1. ABSTRACT
    2. INTRODUCTION
    3. RANDOM NUMBER GENERATORS
    4. CHAOTIC RANDOM NUMBER GENERATION
    5. CHAOTIC MAPS
    6. STATISTICAL TESTS FOR RANDOMNESS
    7. USE OF CHAOTIC RANDOMNESS IN SELECTED ALGORITHMS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  18. Chapter 11: An Integrated Grey Relations Analysis and VIKOR Method for Multi Criteria Decision Making under Fuzzy Environment
    1. ABSTRACT
    2. 1. BACKGROUND AND MOTIVATION
    3. 2. A BRIEF OVERVIEW OF FUZZY LOGIC
    4. 3. A BRIEF OVERVIEW OF THE GREY THEORY
    5. 4. A BRIEF OVERVIEW OF THE VIKOR PROCESS
    6. 5. A NUMERICAL EXAMPLE
    7. 6. CONCLUSION AND REMARKS
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  19. Chapter 12: A Brief Review of Metaheuristics for Document or Text Clustering
    1. ABSTRACT
    2. INTRODUCTION
    3. METAHEURISTICS
    4. DOCUMENT REPRESENTATION
    5. SIMILARITY MEASURES
    6. EVALUATION OF CLUSTERING RESULTS
    7. LITERATURE REVIEW
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  20. Chapter 13: Churn Prediction in Internet Service Provider Companies
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PROBLEM STATEMENT AND METHODOLOGY
    5. CLASSIFICATION
    6. IMPLEMENTATION
    7. COMPUTATIONAL RESULTS
    8. FUTURE RESEARCH
    9. CONCLUSION
    10. REFERENCES
    11. KEY TERMS AND DEFINITIONS
  21. Chapter 14: On the Comparison of Quantitative Predictabilities of Different Financial Instruments
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. DATA
    5. METHODOLOGY
    6. RESULTS
    7. DISCUSSION AND CONCLUSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  22. Chapter 15: Selection of Wavelet Features for Biomedical Signals Using SVM Learning
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. METHODS
    4. 3. RESULTS
    5. 4. CONCLUSION
    6. REFERENCES
  23. Compilation of References
  24. About the Contributors