Earthquake Prediction Research Based on the Mining in Time Series of Groundwater Temperature

摘要

Earthquake prediction has always been an extremely important and difficult research topic. A road map was proposed in this paper to capture useful information for earthquake prediction by exploring the time sequence data of groundwater temperature. Firstly, the triangle extreme points and the trend turning points are employed for the piecewise linear representation of the time series data. Then the segmentation is classified and symbolized by slope, and symbol sequence is simplified further according to the simplification rules. Finally, the earthquake catalogue data and the symbol sequence are jointly preprocessed with a new method to form transactionlike data, which then be treated by association analysis to extract earthquake prediction knowledge. The results of experiment show that this processing flow is an effective way to provide valuable information about earthquake prediction.