運用類神經網路評估混凝土槽溝對震波振幅阻隔效果

Using Network to Estimate the Screening Effect of Surface Waves by Concrete In-Filled Trenches

洪昌祺(Chang-Chi Hung) ； 倪勝火(Sheng-Huoo Ni)

《中國土木水利工程學刊》 25卷4期 (2013/12) Pp. 337-346

https://doi.org/10.6652/JoCICHE.201312_25(4).0008

摘要

本文提出以類神經網路為基礎模式，評估三維混凝土槽溝對震波垂直振幅之阻隔效果。文中採用前授型網路及倒傳遞訓練法則，輸入與槽溝阻隔震波相關參數，經前處理和基因演算法等等參數重要分析後，選擇槽溝斷面、震源與槽溝距離、基礎沉埋深度、填充材料性質等六個參數。並經由Cascade Correlation學習程序，和自動調整學習速率與慣性因子演算法，去改善過去採試誤法決定隱藏層節點個數和網路學習的缺點，建立以平均垂直振幅降低比為輸出值的類神經網路。結果顯示，本文建立之類神經網路模式可模擬三維混凝土槽溝對震波垂直振幅阻隔效果的分析，且預測結果的準確性良好。

關鍵字

類神經網路 ； 振動 ； 震波 ； 槽溝

並列摘要

This paper presents a back-propagation neural network model to estimate the screening effects of vertical amplitude of surface waves by 3-dimensional in-filled trenches. A total of six input parameters are selected by using genetic algorithm with important parameter analysis and pre-processing transfer functions. The parameters are trench dimension, distance between vibrating foundation and trenches, in-filled material property, etc. The number of hidden layer nodes in the network is determined by Cascade Correlation learning processing. The learning parameters of network are determined by Extended-Delta-Bar-Delta algorithm to regulate learning-rate and momentum constant automatically. The output parameter of network is average vertical amplitude reduction rate. The results show that the neural network model is a very good approach in estimating the screening effect of vertical amplitude of seismic wave.

並列關鍵字

neural network ； vibration ； seismic waves ； trench