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Machine Learning in Engineering Analysis and Design: An Integrated Fuzzy Neural Network Learning Model.
- Source :
-
Computer-Aided Civil & Infrastructure Engineering . May99, Vol. 14 Issue 3, p207. 13p. - Publication Year :
- 1999
-
Abstract
- Applying neural network computing to structural engineering problems has received increasing interest, with particular emphasis placed on a supervised neural network with the backpropagation (BP) learning algorithm. In this article, we present an integrated fuzzy neural network (IFN) learning model by integrating a newly developed unsupervised fuzzy neural network (UFN) reasoning model with a supervised learning model in structural engineering. The UFN reasoning model is developed on the basis of a single-layer laterally connected neural network with an unsupervised competing algorithm. The IFN learning model is compared with the BP learning algorithm as well as with a counterpropagation learning algorithm (CPN) using two engineering analysis and design examples from the recent literature. This comparison indicates not only a superior learning performance in solved instances but also a substantial decrease in computational time for the IFN learning model. In addition, the IFN learning model is applied to a complicated engineering design problem involving steel structures. The IFN learning model also demonstrates superior learning performance in a complicated structural design problem with a reasonable computational time. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ARTIFICIAL neural networks
*STRUCTURAL engineering
*BACK propagation
Subjects
Details
- Language :
- English
- ISSN :
- 10939687
- Volume :
- 14
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Computer-Aided Civil & Infrastructure Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 6633654
- Full Text :
- https://doi.org/10.1111/0885-9507.00142