粉煤灰综合利用 FLY ASH COMPREHENSIVE UTILIZATION 2010N0.6 径向基神经网络在粉煤灰混凝土二维和三维碳化 分析中的应用* Application of RBF Neural Network In analysis of 2 Dimensions and 3 Dimensions Carbonation of Fly Ash Concrete 陈树东，李国辉2 (1.南京航空航天大学土木系，江苏南京210016；2.江苏省交通规划设计院，江苏南京210096) 摘要：研究了不同粉煤灰掺量(0%，15%，40%，60%)、不同水灰比(0.3 0.35 0.4)、不强度等级下(C30~C50) 高性能混凝土二维和三维碳化深度；应用多因子输人向量的径向基神经网络(RBF)进行二维和三维碳化深度的预测. 试验表明，采用多因子输人向量的径向基神经网络能够在试验样本数量较少的情况下建立高效准确的预测网络，可以较 好地预测混凝土的碳化深度，其二维和三维碳化深度预测精度比一维精度高，其一维，二维和三维碳化深度的预测值和 试测值相对误差分别为10.9%，5.6%，7.1%.混凝土二维和三维碳化研究对混凝土结构耐久性和寿命预测具有现实意 义. 关键词：混凝土；二维碳化；三维碳化：径向基神经网络 中图分类号：TU528.01 文献标识码：A文章编号：1005-8249(2010)06-0003-04 Chen Shu-dong' Li Guo-hui? (1 Department of Civil Engineering Nanjing University of Aeronautics and Astronautics Nan jing 210016 China 2 Jiangsu Provincial Communications Planning and Design Institute Nan jing 210096 China) Abstract:2 dimensions and 3 dimensions carbonation are studied on different water to cement ratio(0.3.0.35 0.4) different fly ash proportion(0% 15% 20%40% 60%)and different atrength grade(C30-C50).Predict the carbonation depth based on RBF neural network using inputting vector of multiple factor.The experiment indicates 2 dimensions and 3 dimensions carbonation can be very good forecast using RBF Neural Network:at the sanse time the forecasting network of accurate and high efficiency can be built under fewer experiment sample and the precision of 2dimensions 3 dimensions is higher than one dimension precision its relative error of I dimension 2 dime...
径向基神经网络在粉煤灰混凝土二维和三维碳化分析中的应用.pdf
