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Next Generation Artificial Neural Networks and Their Application to Civil Engineering

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Intelligent Computing in Engineering and Architecture (EG-ICE 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4200))

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Abstract

The aims of this paper are: to stimulate interest within the civil engineering research community for developing the next generation of applied artificial neural networks; to identify what the next generation of devices needs to achieve, and; to provide direction in terms of how their development may proceed. An analysis of the current situation indicates that progress in the development of this technology has largely stagnated. Suggestions are made for achieving the above goals based on the use of genetic algorithms and related techniques. It is noted that this approach will require the design of some very sophisticated genetic coding mechanisms in order to develop the required higher-order network structures, and may utilize development mechanisms observed in nature such as growth, self-organization, and multi-stage objective functions. The capabilities of such an approach and the way in which they can be achieved are explored in reference to the truck weigh-in-motion problem.

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Authors and Affiliations

  1. Rinker School, College of Design Construction and Planning, University of Florida, Gainesville, FL, 32611, USA

    Ian Flood

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  1. Ian Flood
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Editor information

Editors and Affiliations

  1. Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 18, 1015, Lausanne, Switzerland

    Ian F. C. Smith

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© 2006 Springer-Verlag Berlin Heidelberg

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Flood, I. (2006). Next Generation Artificial Neural Networks and Their Application to Civil Engineering. In: Smith, I.F.C. (eds) Intelligent Computing in Engineering and Architecture. EG-ICE 2006. Lecture Notes in Computer Science(), vol 4200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11888598_21

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  • DOI: https://doi.org/10.1007/11888598_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46246-0

  • Online ISBN: 978-3-540-46247-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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