碩士 / 國立中興大學 / 土木工程學系 / 87 / This study aims to investigate the applicability of the artificial neural network for predicting the major pertinent parameters of a storm-built beach profile. The prediction model is performed from learning 18 model bar profiles selected from previous large wave tank test. A back-propagation procedure was used to adjust the weights of the connections in the neural network and to minimize the error between the desired outputs and the observed values.
Base on the proposed neural network model, the major geometric parameters for a storm-built bar are predicted well as the wave condition is given. The results show that the neural network model works better then the previous empirical predictions of Silvester and Hsu (1993) and Hsu and Wang (1997). In addition, the neural network also has good performance in the prediction of the storm-built beach profile.
| Identifer | oai:union.ndltd.org:TW/087NCHU0015042 |
| Date | January 1999 |
| Creators | Kuan-Long Pan, 潘冠龍 |
| Contributors | Ching-Piao Tsai, 蔡清標 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 62 |
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