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Pattern Recognition in Industry - Phiroz Bhagat

Pattern Recognition in Industry

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Published: 30th March 2005
Format: PDF
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  • "Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage.

  • *Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry.

  • Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.


Two wave fronts are upon us today: we are being bombarded by an enormous amount of data, and we are confronted by continually increasing technical and business advances.



Ideally, the endless stream of data should be one of our major assets. However, this potential asset often tends to overwhelm rather than enrich. Competitive advantage depends on our ability to extract and utilize nuggets of valuable knowledge and insight from this data deluge. The challenges that need to be overcome include the under-utilization of available data due to competing priorities, and the separate and somewhat disparate existing data systems that have difficulty interacting with each other.



Conventional approaches to formulating models are becoming progressively more expensive in time and effort. To impart a competitive edge, engineering science in the 21st century needs to augment traditional modelling processes by auto-classifying and self-organizing data; developing models directly from operating experience, and then optimizing the results to provide effective strategies and operating decisions. This approach has wide applicability; in areas ranging from manufacturing processes, product performance and scientific research, to financial and business fields.



This monograph explores pattern recognition technology, and its concomitant role in extracting useful knowledge to build technical and business models directly from data, and in optimizing the results derived from these models within the context of delivering competitive industrial advantage. It is not intended to serve as a comprehensive reference source on the subject. Rather, it is based on first-hand experience in the practice of this technology: its development and deployment for profitable application in industry.



The technical topics covered in the monograph will focus on the triad of technological areas that constitute the contemporary workhorses of successful industrial application of pattern recognition. These are: systems for self-organising data; data-driven modelling; and genetic algorithms as robust optimizers.



  • "Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage.

  • Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry.

  • Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.

  • Preface

    Acknowledgments

    About the Author

    Part I Philosophy

    CHAPTER 1: INTRODUCTION

    CHAPTER 2: PATTERNS WITHIN DATA

    CHAPTER 3: ADAPTING BIOLOGICAL PRINCIPLES FOR DEPLOYMENT IN COMPUTATIONAL SCIENCE

    CHAPTER 4: ISSUES IN PREDICTIVE EMPIRICAL MODELING

    Part II Technology

    CHAPTER 5: SUPERVISED LEARNING???CORRELATIVE NEURAL NETS

    CHAPTER 6: UNSUPERVISED LEARNING: AUTO-CLUSTERING AND SELF-ORGANIZING DATA

    CHAPTER 7: CUSTOMIZING FOR INDUSTRIAL STRENGTH APPLICATIONS

    CHAPTER 8: CHARACTERIZING AND CLASSIFYING TEXTUAL MATERIAL

    CHAPTER 9: PATTERN RECOGNITION IN TIME SERIES ANALYSIS

    CHAPTER 10: GENETIC ALGORITHMS

    Part III Case Studies

    CHAPTER 11: HARNESSING THE TECHNOLOGY FOR PROFITABILITY

    CHAPTER 12: REACTOR MODELING THROUGH IN SITU ADAPTIVE LEARNING

    CHAPTER 13: PREDICTING PLANT STACK EMISSIONS TO MEET ENVIRONMENTAL LIMITS

    CHAPTER 14: PREDICTING FOULING/COKING IN FIRED HEATERS

    CHAPTER 15: PREDICTING OPERATIONAL CREDITS

    CHAPTER 16: PILOT PLANT SCALE-UP BY INTERPRETING TRACER DIAGNOSTICS

    CHAPTER 17: PREDICTING DISTILLATION TOWER TEMPERATURES: MINING DATA FOR CAPTURING DISTINCT OPERATIONAL VARIABILITY

    CHAPTER 18: ENABLING NEW PROCESS DESIGN BASED ON LABORATORY DATA

    CHAPTER 19: FORECASTING PRICE CHANGES OF A COMPOSITE BASKET OF COMMODITIES

    CHAPTER 20: CORPORATE DEMOGRAPHIC TREND ANALYSIS

    EPILOGUE

    Appendices

    APPENDIX A1: THERMODYNAMICS AND INFORMATION THEORY

    APPENDIX A2: MODELING

    ISBN: 9780080456027
    ISBN-10: 0080456022
    Format: PDF
    Language: English
    Number Of Pages: 200
    Published: 30th March 2005
    Publisher: Elsevier Science