Building KBES for diagnosing PC pile with artificial neural network

Yi Cherng Yeh, Yau Hwaug Kuo, Deh Shiu Hsu

研究成果: Article同行評審

54 引文 斯高帕斯(Scopus)


Diagnosis of damage of prestressed concrete piles during driving is an important problem in foundation engineering. An effort to build an expert system for the problem is described in this paper. To overcome the bottleneck of knowledge acquisition, an artificial neural network is used as the learning mechanism to transfer engineering experience into usable knowledge. The back-propagation learning algorithm is employed to train the network for extracting knowledge from training examples. The influences of various control parameters (including learning rate and momentum factor) and various network architecture factors (including the number of hidden units and the number of hidden layers) are examined. The results prove that the artificial neural network can work sufficiently as a knowledge-acquisition tool for the diagnosis problem. To apply the knowledge in the trained network, a reasoning strategy that hybridizes forward-and backward-reasoning schemes is proposed to realize the inference mechanism.

頁(從 - 到)71-93
期刊Journal of Computing in Civil Engineering
出版狀態Published - 1993 一月

All Science Journal Classification (ASJC) codes

  • 土木與結構工程
  • 電腦科學應用


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