Geothermal Prediction And Research Of China Based On The Method Of Evidence Weight

In the United States Nevada, Mexico and Japan these areas, the research on geothermaland more logic regression model and knowledge-driven model, these models can very wellthe reaction to predict potential geothermal, but the potential to hot spots of the forecast, thenumber of rate statistics and to hot The space has not been used. Weight of evidence in thedomestic law in the metallogenic prediction and evaluation of the groundwater resourceassessment and forecasting, Debris Flow Hazard Assessment, and other fields have beenapplied and development research, predict and evaluate the potential of geothermal, but notyet in the field of contact geothermal evidence factor space.This thesis using the weights of evidence method to predict and evaluate the potential ofgeothermal in China. Potential geothermal areas to determine the spatial distribution throughthe space of the real hot spot distribution and influencing factors of the surroundinggeothermal research, data and information based on public data can be. Lack of surveyinformation on some of the larger region, this study can be the investigation of these areas toprovide early guidance and reference.The impact of factors used in the analysis of Bouguer gravity anomaly, the epicenter ofthe earthquake fault, and magnetic anomalies of four factors. Magnetic anomalies in theconversion of the evidence layers do not need to do special modifications, while the otherthree factors need to convert the diagram of evidence: the distance to the central area ofBouguer gravity anomaly gradient, the B value fault distance. Evidence of these convertedmaps and magnetic anomaly maps for two different methods for binary processing(descriptive statistics and weights of evidence method) to generate the prediction map; thengenerated forecast map index covering France (I/O), and evidence rights law (WofE)processing to produce the desired map (most likely a geothermal map). Evidence layer factorchi-square tests of independence, and two models of consistency analysis, the model resultsshow that the binary diagram, describe the treatment of the statistical method and the weightof evidence to the expectations generated by the weight of evidence model (WofE) map, beable to accurately description of the hot spots and the direct evidence of Figure spatial relationships.1:800million Chinese evidence layer scale, the forecast map and expectations of the map,in order to verify the weight of evidence model to predict the effectiveness and accuracy ofthe chi-square test and Kappa analysis to evaluate and analyze the model. In addition to theinitial forecast of a large area of China as a whole, the weight of evidence model can beapplied to large-scale layer of evidence to generate forecast map and expectations of the map.But the evidence layer generation process, the need for geothermal evidence factor-relatedparameters to make some adjustments.