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水氡浓度和环境参数的分层神经网络研究
The study of layered neural networks based on radon concentration and environmental parameters in earthquake prediction
【摘要】 采用分层神经网络(LNN)分析地下水的氡浓度,试图给出氡浓度和环境参数之间的函数关系。由于环境(例如:降雨量)对水氡浓度的影响可能是非线性的,与目前时间脉冲响应线性计算方法相比,该方法能够较准确的估计环境参数造成的氡浓度变化。
【Abstract】 LNN had been used to analyze the current radon concentration in groundwater,attempting to find the function relationship between the radon concentration and environmental parameters. The influence of environment(for example:rainfall) on the radon concentration in groundwater may be nonlinear.The LNN can estimate more accurately the radon concentration by environmental parameters change,comparing with the linear computational technique (CLT).The analysis results of Radon observation data from the wells in Xiamen Dongfu show that LNN can accurately find out the change of radon concentration caused by the earthquake from environmental factors(for example:rainfall).In addition,LNN can tell the change of radon concentration by the environmental factors from other factors.
【Key words】 water radon concentration; environmental parameters; neural network; earthquake prediction;
- 【文献出处】 地震地磁观测与研究 ,Seismological and Geomagnetic Observation and Research , 编辑部邮箱 ,2012年Z1期
- 【分类号】P315.7
- 【被引频次】1
- 【下载频次】10