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中文摘要：
基于RBF神经网络的突出优点，利用RBF神经网络研究外加刺对充填体强度的影响规律，利用训练好的RBF神经网络模型对掺入外加剂的充填体强度进行预测分析。训练样本的预测值与实测值的相对误差为0．00％～1．19％；测试样本的预测值与实测值的相对误差为4．76％～6．08％。结果表明：该预测模型不仅可以提高实验工作效率，节省人力、物力，而且具有较高精度。
英文摘要：
The influence of the admixture on the filling body strength is studied using RBF neural network based on its out- standing merits and the filling body strength of admixture bythe trained RBF neural network is predicted and analyzed. The relative error of predicted value and measured value of training samples in RBF neural network model is between 0. 00% - 1. 19%, and the relative error predicted value and measured value of test samples 4.76%-6.08%. The results show that this prediction model not only can improve the efficiency of experimental work and save manpower and materials but also can have higher accuracy.
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