A RBF Neural Network Approach for Fitting Creep Curve of Sandstone

Abstract:

Article Preview

In order to quest an effective approach for predicate the rheologic deformation of sandstone based on some experimental data, an improved approaching model of RBF neural network was set up. The results show, the training time of improved RBF neural network is only about 10 percent of that of the BP neural network; the improved RBF neural network has a high predicating accuracy, the average relative predication error is only 7.9%. It has a reference value for the similar rock mechanics problem.

Info:

Periodical:

Advanced Materials Research (Volumes 171-172)

Edited by:

Zhihua Xu, Gang Shen and Sally Lin

Pages:

274-277

DOI:

10.4028/www.scientific.net/AMR.171-172.274

Citation:

Y. L. Tan and Z. Zhang, "A RBF Neural Network Approach for Fitting Creep Curve of Sandstone", Advanced Materials Research, Vols. 171-172, pp. 274-277, 2011

Online since:

December 2010

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.