摘要
针对地震预测中预测因子高度非线性、训练样本数量有限及分布不均匀的问题,提出采用RBF-BP组合人工神经网络对地震预测因子样本进行建模和预测,并用RBF神经网络初步训练预测因子样本,将训练结果输入BP神经网络,根据期望输出值加强训练。实例分析表明,该预测方法可行并能有效提高地震预测精度。
For the highly non-linear problem of prediction factors, limited and non-uniform distribution training sam- pie in earthquake prediction, RBFBP combined neural network is applied to model and forecast earthquake prediction factor sample. And it trained the predictors sample preliminary with RBF neural network. Then the training result is inputted to BP neural network. Finally, the training is strengthened in terms of expected output. Example results shows that the prediction method is feasible and can improve prediction precision effectively.
出处
《水电能源科学》
北大核心
2011年第12期53-55,共3页
Water Resources and Power
作者简介
聂仙娥（1986-），女，硕士研究生，研究方向为目标传感探测与控制技术，E-mail：niexiane@163．com
