期刊
CONSTRUCTION AND BUILDING MATERIALS
卷 62, 期 -, 页码 102-108出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2014.03.041
关键词
Artificial neural network; Heat treatment; Compression strength; Multiple linear regression
This paper aims to design an artificial neural network model to predict compression strength parallel to grain of heat treated woods, without doing comprehensive experiments. In this study, the artificial neural network results were also compared with multiple linear regression results. The results indicated that artificial neural network model provided better prediction results compared to the multiple linear regression model. Thanks to the results of this study, strength properties of heat treated woods can be determined in a short period of time with low error rates so that usability of such wood species for structural purposes can be better understood. (C) 2014 Elsevier Ltd. All rights reserved.
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