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Industrial Applications of Neural Networks

Project ANNIE Handbook

  • Book
  • © 1992

Overview

Editors:
  1. Ian F. Croall

    1. Harwell Laboratory, AEA Technology, Didcot, Oxon, UK

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    You can also search for this editor in PubMed   Google Scholar

  2. John P. Mason

    1. Harwell Laboratory, AEA Technology, Didcot, Oxon, UK

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Research Reports Esprit (ESPRIT, volume 1)

Part of the book sub series: Project ANNIE (ANNIE)

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Table of contents (7 chapters)

  1. Front Matter

    Pages I-IX
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  2. Introduction

    • Ian F. Croall, John P. Mason
    Pages 1-6

  3. An Overview of Neural Networks

    • Ian F. Croall, John P. Mason
    Pages 7-16

  4. Implementations of Neural Networks

    • Ian F. Croall, John P. Mason
    Pages 17-54

  5. Pattern Recognition

    • Ian F. Croall, John P. Mason
    Pages 55-117

  6. Control Applications

    • Ian F. Croall, John P. Mason
    Pages 119-159

  7. Optimisation

    • Ian F. Croall, John P. Mason
    Pages 161-218

  8. Methodology

    • Ian F. Croall, John P. Mason
    Pages 219-234

  9. Back Matter

    Pages 235-297
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Keywords

About this book

Neural network technology encompasses a class of methods which attempt to mimic the basic structures used in the brain for information processing. Thetechnology is aimed at problems such as pattern recognition which are difficult for traditional computational methods. Neural networks have potential applications in many industrial areas such as advanced robotics, operations research, and process engineering. This book is concerned with the application of neural network technology to real industrial problems. It summarizes a three-year collaborative international project called ANNIE (Applications of Neural Networks for Industry in Europe) which was jointly funded by industry and the European Commission within the ESPRIT programme. As a record of a working project, the book gives an insight into the real problems faced in taking a new technology from the workbench into a live industrial application, and shows just how it can be achieved. It stresses the comparison between neural networks and conventional approaches. Even the non-specialist reader will benefit from understanding the limitations as well as the advantages of the new technology.

Editors and Affiliations

  • Harwell Laboratory, AEA Technology, Didcot, Oxon, UK

    Ian F. Croall, John P. Mason

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