Overview
- State of the art of Neural Networks in real-world, safety-critical systems
- Presents Neural Network applications in safety related areas, ranging from aerospace industry and steam power turbines to the automotive industry
- Provides a better understanding of the practical requirements for developing and deploying neuro-adaptive systems
Part of the book series: Studies in Computational Intelligence (SCI, volume 268)
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Table of contents (12 chapters)
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Front Matter
Keywords
About this book
"Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems.
Editors and Affiliations
Bibliographic Information
Book Title: Applications of Neural Networks in High Assurance Systems
Editors: Johann Schumann, Yan Liu
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-10690-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2010
Hardcover ISBN: 978-3-642-10689-7Published: 28 February 2010
Softcover ISBN: 978-3-642-26269-2Published: 04 May 2012
eBook ISBN: 978-3-642-10690-3Published: 10 March 2010
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 248
Number of Illustrations: 99 b/w illustrations
Topics: Mathematical and Computational Engineering, Artificial Intelligence, Automotive Engineering, Industrial and Production Engineering