摘要
对地震前兆观测时间序列的混沌性态及其产生的根源进行了探讨。根据小波变换良好的时、频局部化特征和分形维数的变化特征,从小波分析多尺度分解的角度出发结合分形理论探讨了地震前兆混沌时间序列的异常识别问题。对几个实例的研究表明,大多数时间段内时间序列小波变换系数的分维—尺度变化曲线呈光滑、缓慢减小变化,有异常信息时段的时间序列小波变换系数的分维—尺度变化曲线变化的主要特点是曲线具有峰值,并出现了曲线先是由高向低,然后再由低向高变化,在某一尺度处达到峰值后再缓慢减小的情况。异常出现的时间在震前约2个月至1年。将小波变换与分形理论结合起来研究地震问题,不仅开拓了地震科学研究的新领域,同时也是对小波变换及分形理论应用的延拓。
In this paper, the chaotic condition and chaotic root of the earthquake precursor observation time series are discussed, and the problem of how to recognize anomalous element of the earthquake precursor observation time series is studied from the point of view of wavelet transform with multi-scale analysis combining with fractal theory according to good localized characteristic of time and frequency of wavelet transform and the variation characteristic in fractal dimension. It is indicated that the variation of fractal dimension of time series＇ wavelet transform coefficient with scale shows smoothly and slowly reductive variation in most of time intervals. In anomalous time intervals, the peculiarity of the variation curves shows the instance of peak value, in which the curve varies from high value to low value first and then varies from low value to a relatively high value and then it slowly reduces at a peak value. The anomalous information is checked out two months to one year before the earthquakes in the examples. To study earthquake problem by combining wavelet theory with fractal theory is not only the exploitation for a new field of earthquake research, but also the continuation for the application of wavelet transform and fractal theory.
出处
《防灾减灾工程学报》
CSCD
2007年第2期211-216,共6页
Journal of Disaster Prevention and Mitigation Engineering
基金
江苏省科技计划资助项目(BS2004045)
关键词
地震前兆
多尺度分维
异常识别
earthquake precursor
multi-scale fractal demension
anomaly recognition
