The Research Of Bayesian Networks Application For Comprehensive Earthquake Prediction

Both of seismological practice and theory indicate that the generation of earthquake is an extremely complicated process. With so much anfractuous and correlation, many uncertainty factors and much uncertainty information in complex coupling precursory anomalies, the earthquake prediction is very difficult. The researchers in this field always try their best in investigating decision models, which can quickly fuse precursory anomalies related to comprehensive earthquake prediction, and effectively handle the uncertainty information. This dissertation deeply investigates several key techniques including knowledge expression of Bayesian Networks, model construction of Bayesian Networks, and Bayesian Networks update algorithms. Also it presents the designs and implemental methods of Bayesian networks application for comprehensive earthquake prediction, especially Network Negotiatory Comprehensive Earthquake Prediction GDSS. The main points of research can be summarized as follows. 1. The main difficulties faced by comprehensive earthquake prediction are analyzed, and the major limits of existed comprehensive earthquake prediction decision models and methods are summarized. Then the Bayesian network application method for comprehensive earthquake prediction is put forward, and several advantages and the principal goals of this method are pointed out. 2. In order to handle the construction and reasoning problems, a hierarchy construction method for Comprehensive Earthquake Prediction Bayesian Networks Model is established, which is based on seismological experts' experiences and knowledge, and it also provides a systemic principle for Comprehensive Earthquake Prediction Bayesian Networks Model construction, which deals with complex precursory anomalies. 3. This dissertation deeply dose researches about implement methods of Bayesian networks application for comprehensive earthquake prediction, especially Network Negotiatory Comprehensive Earthquake Prediction GDSS. An analyzer for Comprehensive Earthquake Prediction Bayesian Networks Model is developed, which can construct and modify Bayesian networks through visual interfaces, and its inference module is based on improved bucket tree eliminating algorithm. In conclusion, this paper deeply researches the applications of Bayesian networks for comprehensive earthquake prediction, proposes a Comprehensive Earthquake Prediction Bayesian Networks Model, which was successfully applied in the Network Negotiatory Comprehensive Earthquake Prediction GDSS.