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Next Generation Artificial Neural Networks and Their Application to Civil Engineering

  • Ian Flood
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4200)

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.

Keywords

Artificial Neural Network ASCE Journal Input Data Stream Cial Neural Network Strain Reading 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ian Flood
    • 1
  1. 1.Rinker School, College of Design Construction and PlanningUniversity of FloridaGainesvilleUSA

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