用神经网络预测矿渣与粉煤灰混凝土的强度  

To forecast strength of slag and fly ash concrete with neural network

作　　者：赵兴君[1] 张兰芳[1] 岳瑜 

机构地区：[1]辽宁工程技术大学土木建筑工程学院,辽宁阜新123000 [2]重庆钢铁集团建设公司,重庆400084

出　　处：《辽宁工程技术大学学报（自然科学版）》2003年第6期797-799,共3页Journal of Liaoning Technical University (Natural Science)

摘　　要：利用目前神经网络中使用最多的BP网络的模型来预测矿渣粉煤灰混凝土的3天、28天的抗压强度。结果表明,由于神经网络具有很强的非线性表现能力,计算精度高,预测能力强,将神经网络方法应用于矿渣、粉煤灰混凝土的强度预测中,可为工程人员提供很大的方便,以指导生产,适应时代发展的要求。This paper uses BP neural network which is used extensively at present in neural net model to forecast the strength of concrete which is added to slag and fly ash. Because neural network has very strong non-liner ability, so the result shows that its precision of caculation is high. At the same time, its forecasting ability is high. If we use this method to forecast the strength of concrete which would be added to slag and fly ash, it will offer many conveniences to engineering people who guide production in order to meet the demand of development of the present times.

关 键 词：神经网络 强度预测 矿渣 粉煤灰混凝土 

分 类 号：TQ536.4[化学工程—煤化学工程] TP183[自动化与计算机技术—控制理论与控制工程]