Development of a Predictive System for Anticipating Earthquakes using Data Mining Techniques

Abstract

Objectives: A wide variety of disasters occur across the globe, prediction of such disaster is the requisite for early precaution and evacuation process. Prediction of earthquake could be achieved using precursors or seismographic data but all such methods can be carried out only by the domain experts (seismologist). Methods: Data mining methods have been used in a wide variety of applications and in various domains. It allows prediction of performance and expected progression which enables derivation of rational decisions. Anticipating earthquake using previous earthquake history data can be achieved using data mining concepts. In this paper, a prediction model is proposed for anticipating earthquakes by applying clustering and association rule mining on earthquake history data. Initially, the data is collected and they are clustered, this clustered data is passed to next phase where frequent patterns are obtained by applying association rule mining, finally by using the obtained pattern, the upcoming earthquakes are predicted by performing rule matching. Findings: This paper describes a predictive model employing significant earthquake data and mining techniques which predicts the fore coming earthquake. Applications: This prediction model can be used to predict various seismic events and also they can be used for making prediction in other fields by employing appropriate dataset.