期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 36, 期 3, 页码 5807-5812出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2008.07.004
关键词
Knowledge discovery; Genetic algorithms; Operation tree; Material; Concrete
类别
资金
- National Science Council, Taiwan [96-2221-E-216-032]
This study proposed a novel knowledge discovery method, Genetic Operation Tree (GOT), which is composed of operation tree (OT) and genetic algorithm (GA), to automatically produce self-organized formulas to predict compressive strength of High-Performance Concrete. In GOT, OT plays the architecture to represent an explicit formula, and GA plays the optimization mechanism to optimize the OT to fit experimental data. Experimental data from several different sources were used to evaluate the method. The results showed that GOT can produce formulas which are more accurate than nonlinear regression formulas but less accurate than neural network models. However, neural networks are black box models, while GOT can produce explicit formulas, which is an important advantage in practical applications. (C) 2008 Elsevier Ltd. All rights reserved.
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