CAJ | 학술논문

传统BP神经网络存在局部极小值、学习算法收敛速度慢、网络结构难以确定等缺点，因此采用改进的BP神经网络分析地下工程围岩的稳定性。将岩石单轴饱和抗压强度、岩石质量指标、岩体的完整性系数、结构面的强度系数、地下水渗流量作为围岩的分类指标，利用附加动量因子、L-M优化算法与Nguyen-Widrow初始化算法相结合的改进BP神经网络建立围岩稳定性的分类预测模型，并运用MATLAB对学习样本进行分类识别，确定地下工程围岩的岩体等级，并结合平均影响值特征筛选法确定影响围岩稳定性的主导因素。实例分析结果表明：岩体的质量、强度以及所处的状态对围岩的稳定起主导作用，结构面产状和性状则为次级影响因素。
전통BP신경망락존재국부겁소치、학습산법수렴속도만、망락결구난이학정등결점，인차채용개진적BP신경망락분석지하공정위암적은정성。장암석단축포화항압강도、암석질량지표、암체적완정성계수、결구면적강도계수、지하수삼류량작위위암적분류지표，이용부가동량인자、L-M우화산법여Nguyen-Widrow초시화산법상결합적개진BP신경망락건립위암은정성적분류예측모형，병운용MATLAB대학습양본진행분류식별，학정지하공정위암적암체등급，병결합평균영향치특정사선법학정영향위암은정성적주도인소。실례분석결과표명：암체적질량、강도이급소처적상태대위암적은정기주도작용，결구면산상화성상칙위차급영향인소。
Traditional BP network has its shortcomings of local minimum,the slow convergence speed of learning algorithm and the difficulty defi-ning the structure. Therefore,it analyzed the stability of surrounding rock of underground engineering by using improved BP neural network. Using single-axle saturated rock's compression strength,rock quality designation,integrity coefficient of rock mass,strength coefficient of structural plane and seepage discharge of groundwater as classification index of surrounding rock,using improved BP neural network with momentum factor,L-M optimization algorithm,Nguyen-Widrow method to establish a forecasting model of the stability of surrounding rock,classifying the learning sample by using MATLAB program,confirming the grade of rock mass. Determining main factors of affecting the stability of the surrounding rock by com-bined MIV algorithm selection,the results show that the leading roles of rock stability are rock mass quality,strength and the state. Structural plane occurrence and characters are secondary factors.