人工神经网络算法在岩土工程中的应用分析

Analysis on the Application of Artificial Neural Network Algorithm in Geotechnical Engineering

人工神经网络算法作为一种机器学习技术,能够模拟人类大脑的生理结构及工作机制。文章对人工神经网络算法的类别和工作原理进行了分析阐述,重点对分别属于前反馈型模型、后反馈型模型及自适应竞争模型的反向传播人工神经网络算法、Hopfield神经网络算法和自组织映射人工神经网络算法进行介绍,进而分析上述三种人工神经网络算法在岩土工程中的实际应用。人工神经网络算法能对土壤进行准确分类,对岩石进行准确分组,并准确预测岩石和土壤形变,对边坡的稳定性和路基沉降的预测准确性高,在岩土工程中有重要的应用价值。

As a machine learning technology,artificial neural network algorithm can simulate the physiological structure and working mechanism of the human brain.The classification and working principle of artificial neural network algorithm are analyzed and expounded,focusing on The back-propagation artificial neural network algorithm,Hopfield neural network algorithm and self-organizing map artificial neural network algorithm,which belong to the front feedback model,the back feedback model and the adaptive competition model respectively.The practical application of the above three artificial neural network algorithms in geotechnical engineering is analyzed.Artificial neural network algorithm can accurately classify soil,group rocks,and predict rock and soil deformation.It has high prediction accuracy for slope stability and subgrade settlement,and has important application value in geotechnical engineering.