Industrial Applications of Neural Networks

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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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.

• algorithms
• artificial intelligence
• cognition
• control
• heuristics
• learning
• linear optimization
• neural networks
• operations research
• optimization
• pattern recognition
• proving
• robot
• robotics
• scheduling
• complexity

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

  Ian F. Croall, John P. Mason

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