Intelligent design method for soft rock engineering supporting based on tow layer support vector machines
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摘要: 將一種機器學習算法——支持向量機引入到軟巖工程支護設計領域,并根據問題需要提出了一種支持向量機回歸算法且編制了相應的計算程序.工程算例證明,這種算法在學習樣本數量很少的情況下就可以得到很高的預測精度,且具有推廣性能好的優點,避免了人工神經元由于存在過學習問題而帶來的網絡參數難以確定的弊病,為類似工程的支護設計提供了一種新的途徑.Abstract: A machine learning algorithm——Support Vector Machines (SVM) was introduced into the field of soft rock engineering supporting design. An improved Support Vector Machines Regression (SVR) algorithm was presented to meet the needs of this problem and the corresponding calculation code was programmed, It is concluded that a high degree of prediction accuracy and a very good generalization can be obtained with small quantity of learning samples using this algorithm from the calculated results of an engineering instance. It can avoid the overfitting problem of artificial neural network (ANN) which brings the difficulty in determining the parameters of ANN. It facilitates users to a great extent and provides a new way in the supporting design of similar engineering.
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