An Innovative Data Mining Approach for Determine Earthquake Probability Based on Linear Regression Algorithm

Abstract

Earthquake (EQ) causes many damages to our environment, this paper proposes a new approach to find the Earthquake probability (EQP) using linear regression (LR-EQP) is to minimize this extensive problem with the help of geological data by predicting the intended probability of the level of EQ. This approach is to take the all the geological information which are responsible for EQ such as to create pressure on the land like density of population (DP), soil type (ST), combustible elements (CE), specify the place use latitude and longitude (Lat-Long), distance from nearest tectonic plate (TP). Since TP is the divided part of earth which move independently and responsible earth's seismic activity and LR-EQP deploy these geological data, so LR-EQP approach can determine the EQP easily and accurately. Earthquake prediction using data mining is a process, which uses only three factors: (a) ground water level, (b) chemical changes and (c) radon gas in ground water. But this is a slow approach to determine EQP because in general these factors cannot be determined so easily. LR-EQP can be used for any region by targeting the TP area. This data model can be used also for mobile application for easily detecting the probability of earthquake