摘要
为了对未来地震趋势进行预测,提出一种BP神经网络预测方法。利用Matlab建立BP神经网络模型,并以滇西南地震数据为学习样本对网络模型进行了训练和仿真测试研究。研究结果表明,利用BP神经网络模型预报的地震震级与实际震级误差在8%以下,说明所建模型具有较好的适应性和预报精度。该方法对地震震级的预测具有一定的指导作用和参考价值。
To predict the earthquake trend in future, the predictive method based on BP neural network is proposed. The BP neural network model is established by adopting Matlab, and the model is trained by using the data from southwest of Yunnan province as the learning samples, then the model is studied with simulation test. The results of research demonstrate that the error between actual magnitude and the magnitude predicted using BPNN is less than 8%, and the model possesses better adaptability and predictive precision. The method provides reference and guidance to magnitude prediction.
出处
《自动化仪表》
CAS
北大核心
2012年第6期12-14,17,共4页
Process Automation Instrumentation
关键词
BP神经网络
地震预测
网络模型
仿真
震级误差
Back propagation neural network Earthquake prediction Network model Simulation Magnitude error
