CAJ | 학술논문

矿建工程投资数额大、周期长,井筒工程造价所占比重大,投资估算准确性对决策至关重要.在分析井筒工程施工特点的基础上,甄选7个工程特征指标,利用Matlab提供的神经网络函数构建7个输入指标、1个输出指标的BPNN模型来预测井筒工程造价估算值.结果表明,利用BPNN模型预测,只要井筒工程特征选取合理,BPNN模型的参数设置准确,BPNN神经网络能较快地达到设定的目标,预测精度在±10%以内,能够为煤矿建设的决策提供可靠依据.
광건공정투자수액대、주기장,정통공정조개소점비중대,투자고산준학성대결책지관중요.재분석정통공정시공특점적기출상,견선7개공정특정지표,이용Matlab제공적신경망락함수구건7개수입지표、1개수출지표적BPNN모형래예측정통공정조개고산치.결과표명,이용BPNN모형예측,지요정통공정특정선취합리,BPNN모형적삼수설치준학,BPNN신경망락능교쾌지체도설정적목표,예측정도재±10%이내,능구위매광건설적결책제공가고의거.
Mine construction has the characteristics of huge investment,long cycle,the accuracy of the investment estimate for investment decisions is essential. Base on analyzing shaft construction,selects 7 index of engineering characteristics,uses Matlab to build BPNN model including 7 input and 1 output index for predicting the shaft project investment. The results show that,as long as the selecting of project characteristics and BPNN model parameter settings are appropriate and accurate,the neural network method can quickly achieve the target,the prediction accuracy could reach± 10% or less,provides reliable basis for making decision of mine construction.