Neural Networks in Bioprocessing and Chemical Engineering

Neural Networks in Bioprocessing and Chemical Engineering

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Description

Neural networks have received a great deal of attention among scientists and engineers. In bioprocessing and chemical engineering, neural computing has moved from pioneering projects toward mainstream industrial applications. This book introduces the fundamental principles of neural computing, and is the first to focus on its practical applications in bioprocessing and chemical engineering. Examples, problems, and ten detailed case studies demonstrate how to develop, train, and apply neural networks. A disk containing input data files for all illustrative examples, case studies, and practice problems provides the opportunity for hands-on experience. An important goal of the book is to help the student or practitioner learn and implement neural networks quickly and inexpensively using commercially available, PC-based software tools. Detailed network specifications and training procedures are included for all neural network examples discussed in the book. Features: * Each chapter contains an introduction, chapter summary, references to further reading, practice problems, and a section on nomenclature.
* Includes a PC-compatible disk containing input data files for examples, case studies, and practice problems. * Contains an extensive glossary, explaining terminology used in neural network applications in science and engineering. * Provides examples, problems, and ten detailed case studies of neural computing applications.
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Product details

  • Mixed media product | 400 pages
  • 180 x 261 x 31mm | 1,116g
  • Academic Press Inc
  • San Diego, United States
  • English
  • glossary, index
  • 0120830302
  • 9780120830305

Table of contents

Introduction to neural networks; fundamental and practical aspects of neural computing; classification - fault diagnosis and feature categorization; prediction and optimization; process forecasting, modelling and control of time-dependent systems; development of expert networks - a hybrid system of expert systems and neural networks.
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