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High-precision chaotic radial basis function neural network model:Data forecasting for the earth electromagnetic signal before a strong earthquake

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Geoscience Frontiers 2022年第1期13卷 364-373页

作者： Guocheng Hao Juan Guo Wei Zhang Yunliang Chen David AYuen school of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China school of Computer science China University of GeosciencesWuhan 430074China Department of Mathematics Duke UniversityDurhamNC 27708USA Department of Applied Physics and Applied Mathematics Columbia UniversityNew YorkNY 10027USA

The earth’s natural pulse electromagnetic field data consists typically of an underlying variation tendency of intensity and *** change tendency may be related to the occurrence of earthquake *** of the underlying intensity trend plays an important role in the analysis of data and disaster *** chaos theory and the radial basis function neural network,this paper proposes a forecasting model of the chaotic radial basis function neural network to conduct underlying intensity trend forecasting by the earth’s natural pulse electromagnetic field *** main strategy of this forecasting model is to obtain parameters as the basis for optimizing the radial basis function neural network and to forecast the reconstructed earth’s natural pulse electromagnetic field *** verification experiments,we employ the 3 and 6 days’data of two channels as training samples to forecast the 14 and 21-day earth’s natural pulse electromagnetic field data *** to the forecasting results and absolute error results,the chaotic radial basis function forecasting model can fit the fluctuation trend of the actual signal strength,effectively reduce the forecasting error compared with the traditional radial basis function ***,this network may be useful for studying the characteristics of the earth’s natural pulse electromagnetic field signal before a strong earthquake and we hope it can contribute to the electromagnetic anomaly monitoring before the earthquake.

关键词： earth’s natural pulse electromagnetic field Chaos theory Radial Basis Function neural network Forecasting model

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