• Next generation artificial neu...

Result: Next generation artificial neural networks and their application to civil engineering

Title:
Next generation artificial neural networks and their application to civil engineering
Authors:
FLOOD, Ian
Source:
Intelligent computing in engineering and architecture (13th EG-ICE Workshop 2006, Ascona, Switzerland, June 25-30, 2006)0EG-ICE 2006. :206-221
Publisher Information:
Berlin; New York: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 18 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Batiment. Travaux publics, Buildings. Public works, Algorithme génétique, Genetic algorithm, Algoritmo genético, Autoorganisation, Self organization, Autoorganización, Camion, Lorry, Camión, Fonction objectif, Objective function, Función objetivo, Génie civil, Civil engineering, Ingeniería civil, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Programmation multiobjectif, Multiobjective programming, Programación multiobjetivo, Réseau neuronal, Neural network, Red neuronal
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Rinker School, College of Design Construction and Planning, University of Florida, Gainesville, FL 32611, United States
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=19152997
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Building. Public works. Transport. Civil engineering

Computer science; theoretical automation; systems
Accession Number:
edscal.19152997
Database:
PASCAL Archive

Further Information

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.