- "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 operat
This book is ideal for engineers, plant managers, business strategists, consultants, fund managers, financial analysts, R&D managers, product formulators and developers directly involved with the process industry.
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<B
- No. of pages:
- © Elsevier Science 2005
- 30th March 2005
- Elsevier Science
- eBook ISBN:
- Hardcover ISBN:
- Paperback ISBN:
"Phiroz Bhagat tackles the important problem of data inundation in this book, and offers innovative strategies using pattern recognition theory in practical applications. There are good ideas here, well worth exploring." Peter Likins President, University of Arizona