A Study on Earthquake Prediction Using Neural Network Algorithms - Mohankumar, K; Sangeetha, K (International Journal of Computer Sciences and Engineering, 2025)
Data mining is a result of advancement in information technology. It is a progression of discovering knowledge from large databases. Earthquake prediction is one of the major issue in seismology. The intention of the prediction is to make possible emergency measures to reduce death and demolition, breakdown by giving forewarning about earthquake. Now a day’s neural network plays a vital role in the prediction of earthquake. Back propagation is a neural network learning algorithm is used to analyze the relationship between the earthquakes. This analysis is performed with the parameters such as date, time of the event, latitude, longitude, depth and magnitude of past earth quake events. This set of data converted into seismic indicators by doing mathematical calculations and given to the input layer of neural network. The output of neural network is used for prediction. In this paper, various research articles deals with earthquake which are using neural network algorithms are studied and the accuracy rate of the prediction is compared