人民黄河2016，Vol.38Issue(3)：108-111,4.DOI:10.3969/j.issn.1000-1379.2016.03.029
基于神经网络的节理岩体单轴强度预测
Jointed Rock Uniaxial Strength Prediction Based on Neural Network
摘要
Abstract
Based on the uniaxial compression test results of jointed rock on RMT⁃150C rock mechanics test system, the factors influencing uniaxial compressive strength of joint rock had been analyzed. The uniaxial compressive strength of joint rock was related to joint continuity, joint angle and joint number and it's a complex nonlinear relationship. The peak strength of jointed rocks with same joint continuity reached to the highest value as joint angle is 0, the peak strength of jointed rocks with same joint angle decreased with the increase of joint continuity. Considering the influence of various factors on joint rock uniaxial compressive strength, the BP neural net model had been build to predict uniaxial compressive strength of joint rock and optimized by genetic algorithm. Through studying and fitting the sample data of rock uniaxial compression test, the uniaxial compressive strength of joint rock could be predicted well by BP neural net model optimized by genetic algorithm.关键词
节理岩体/遗传算法/BP神经网络/单轴压缩强度Key words
jointed rock mass/genetic algorithm/BP neural network/uniaxial compressive strength分类
建筑与水利引用本文复制引用
胡安龙,王孔伟,邓华锋,常德龙,肖志勇,李春波..基于神经网络的节理岩体单轴强度预测[J].人民黄河,2016,38(3):108-111,4.基金项目
国家自然科学基金资助项目（51309141，51279091）；水利部公益性科研专项（201401029）；三峡大学研究生科研创新基金资助项目（2015CX036）。 （）
