The paper introduces the anomalies observed by digital tiltmeter, cross-fault deformation meter, 4-component borehole strainmeter and geothermometer before May 12, 2008, Ms8.0 Wenchuan earthquake, Sichuan. The digital...The paper introduces the anomalies observed by digital tiltmeter, cross-fault deformation meter, 4-component borehole strainmeter and geothermometer before May 12, 2008, Ms8.0 Wenchuan earthquake, Sichuan. The digital tiltmeter installed in the epicentral region in Shifang County recorded the tilt anomalies 15 days before the earthquake with variation amplitude of 3.7 times larger than the annual deviation of 2007. The cross-fault deformation meter installed at Zimakua station on the Xianshuihe-Anninghe fault zone detected displacement anomaly occurring since 2006 with the variation amplitude exceeding the cumulative value of the last ten years. Five borehole strainmeter stations in the Chongqing section of Three Gorges Reservoir area observed unconventional strain changes occurring in the period from May 1 through 12, 2008. Among them, the strainmeter at Wanzhou station recorded the great compression strain rate on the EW component at 14：00 o＇clock of May 10, and the anomaly amplitude was so large that the instrument output exceeded its dynamic range, corresponding to a level of -10^4 nanostrains. The geothermometers installed in Xi＇an, Chongqing and Xichang recorded the sudden temperature changes from November 2007 to January 2008 with the variation amplitudes several times larger than the ordinary deviation. The above phenomena and the criteria for distinguishing the anomalies from background fluctuations are discussed in this paper.展开更多
Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is ...Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Station, the bulk strain observation of Liyang station as examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.展开更多
基金supported by the fundamental research fund of Institute of Crustal Dynamics,China Earthquake Administration(Grant No.ZDJ2008-33)
文摘The paper introduces the anomalies observed by digital tiltmeter, cross-fault deformation meter, 4-component borehole strainmeter and geothermometer before May 12, 2008, Ms8.0 Wenchuan earthquake, Sichuan. The digital tiltmeter installed in the epicentral region in Shifang County recorded the tilt anomalies 15 days before the earthquake with variation amplitude of 3.7 times larger than the annual deviation of 2007. The cross-fault deformation meter installed at Zimakua station on the Xianshuihe-Anninghe fault zone detected displacement anomaly occurring since 2006 with the variation amplitude exceeding the cumulative value of the last ten years. Five borehole strainmeter stations in the Chongqing section of Three Gorges Reservoir area observed unconventional strain changes occurring in the period from May 1 through 12, 2008. Among them, the strainmeter at Wanzhou station recorded the great compression strain rate on the EW component at 14：00 o＇clock of May 10, and the anomaly amplitude was so large that the instrument output exceeded its dynamic range, corresponding to a level of -10^4 nanostrains. The geothermometers installed in Xi＇an, Chongqing and Xichang recorded the sudden temperature changes from November 2007 to January 2008 with the variation amplitudes several times larger than the ordinary deviation. The above phenomena and the criteria for distinguishing the anomalies from background fluctuations are discussed in this paper.
文摘Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Station, the bulk strain observation of Liyang station as examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.
