This paper summarizes the layout of the Yunnan seismic ELF electromagnetic observation network,site selection,ELF electromagnetic instrument system,data processing and other construction. The principle and method of u...This paper summarizes the layout of the Yunnan seismic ELF electromagnetic observation network,site selection,ELF electromagnetic instrument system,data processing and other construction. The principle and method of using the ELF electromagnetic wave technique to monitor and predict earthquakes are expounded. The long term monitoring of ELF electromagnetic fields is carried out in the Yunnan earthquake prone area,and at the same time,the changes in electrical parameters and spatial electromagnetic fields of the regional crustal medium structure are monitored. The functions such as automatic,quasi real time, remote monitoring, network monitoring, data processing specialization, data service,data sharing and industrialization of the ELF electromagnetic observation data have been realized. In order to capture the deep electromagnetic precursory information of the earthquakes,service for earthquake prediction research,which has broad application prospects and development potential. Through the research of the seismicity of Yunnan in the trial run period of the project,the preliminary results of the extreme low frequency electromagnetic observation of the Yunnan earthquake in recent years are given. The electromagnetic precursors and the electromagnetic effects of the Yangbi earthquake are recorded. In the 3-month period before the earthquake,the power spectrum of the electric and magnetic fields,the apparent resistivity and the impedance phase in the observed signals are all abnormal,and gradually increased with time. The maximum value is reached 20 days before the earthquake,and an earthquake occurs when the change is restored to normal.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
On the basis of the past research and utilization on the windows and belts of seismic regime, the seismic regime network which has been supposed and proved in the past is set up by using the monthly frequency data of ...On the basis of the past research and utilization on the windows and belts of seismic regime, the seismic regime network which has been supposed and proved in the past is set up by using the monthly frequency data of small earthquakes from 1970 to 1991 over the whole country. Through checking its function in practice, it is found that the spatial distribution of precursor information is not an isolate window or belt, but a broad precursor information field before the Ms≥7. 0 earthquakes in China and its nearby regions. According to the windows and belts in the field, synchronism and generality of initial time and place of prediction, the comprehensive prediction of activity time periods of groups of strong earthquakes and the detail method of correspondence of groups are proposed. After restrict mathematical test, 10 prediction methods for references are set forth, in which two best methods are selected as references for the whole case prediction in one to three years. Some related problems are discussed at the end of this paper.展开更多
The field of neural network has found solid application in the past ten years and the field itself is still developing rapidly. Neural network is composed of many simple elements operating in parallel. A neural netwo...The field of neural network has found solid application in the past ten years and the field itself is still developing rapidly. Neural network is composed of many simple elements operating in parallel. A neural network can be trained to perform a particular mapping and this is the basis of its application to practical problems. In this paper, new methods for predicting the strong earthquakes are presented based on neural network. Neural network learns from existing earthquake sequences or earthquake precursors how to make medium and short term prediction of strong earthquakes. This paper describes two neural network prediction models. One is the model based on earthquake evolution sequences, which is applied to the modeling of the magnitude evolution sequences in the Mainland of China, the other is based on earthquake precursors, which is applied to the modeling of the occurrence time of strong earthquakes in North China. Test results show that the prediction methods based on neural networks are efficient, and convenient. They would find more application in the future.展开更多
基金supported by the National Development and Reform Commission,PRCthe elventh “Five-year Plan” National Major Scientific and Technological Infrastructure Construction Projects
文摘This paper summarizes the layout of the Yunnan seismic ELF electromagnetic observation network,site selection,ELF electromagnetic instrument system,data processing and other construction. The principle and method of using the ELF electromagnetic wave technique to monitor and predict earthquakes are expounded. The long term monitoring of ELF electromagnetic fields is carried out in the Yunnan earthquake prone area,and at the same time,the changes in electrical parameters and spatial electromagnetic fields of the regional crustal medium structure are monitored. The functions such as automatic,quasi real time, remote monitoring, network monitoring, data processing specialization, data service,data sharing and industrialization of the ELF electromagnetic observation data have been realized. In order to capture the deep electromagnetic precursory information of the earthquakes,service for earthquake prediction research,which has broad application prospects and development potential. Through the research of the seismicity of Yunnan in the trial run period of the project,the preliminary results of the extreme low frequency electromagnetic observation of the Yunnan earthquake in recent years are given. The electromagnetic precursors and the electromagnetic effects of the Yangbi earthquake are recorded. In the 3-month period before the earthquake,the power spectrum of the electric and magnetic fields,the apparent resistivity and the impedance phase in the observed signals are all abnormal,and gradually increased with time. The maximum value is reached 20 days before the earthquake,and an earthquake occurs when the change is restored to normal.
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.
文摘On the basis of the past research and utilization on the windows and belts of seismic regime, the seismic regime network which has been supposed and proved in the past is set up by using the monthly frequency data of small earthquakes from 1970 to 1991 over the whole country. Through checking its function in practice, it is found that the spatial distribution of precursor information is not an isolate window or belt, but a broad precursor information field before the Ms≥7. 0 earthquakes in China and its nearby regions. According to the windows and belts in the field, synchronism and generality of initial time and place of prediction, the comprehensive prediction of activity time periods of groups of strong earthquakes and the detail method of correspondence of groups are proposed. After restrict mathematical test, 10 prediction methods for references are set forth, in which two best methods are selected as references for the whole case prediction in one to three years. Some related problems are discussed at the end of this paper.
文摘The field of neural network has found solid application in the past ten years and the field itself is still developing rapidly. Neural network is composed of many simple elements operating in parallel. A neural network can be trained to perform a particular mapping and this is the basis of its application to practical problems. In this paper, new methods for predicting the strong earthquakes are presented based on neural network. Neural network learns from existing earthquake sequences or earthquake precursors how to make medium and short term prediction of strong earthquakes. This paper describes two neural network prediction models. One is the model based on earthquake evolution sequences, which is applied to the modeling of the magnitude evolution sequences in the Mainland of China, the other is based on earthquake precursors, which is applied to the modeling of the occurrence time of strong earthquakes in North China. Test results show that the prediction methods based on neural networks are efficient, and convenient. They would find more application in the future.
