Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Nikhil Satish
SRM University
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

 1 
Earthquake trend prediction using long short-term memory RNN Tanvi Bhandarkar; Vardaan K; Nikhil Satish; S. Sridhar; R. Sivakumar; Snehasish Ghosh
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (704.597 KB) | DOI: 10.11591/ijece.v9i2.pp1304-1312

Abstract

The prediction of a natural calamity such as earthquakes has been an area of interest for a long time but accurate results in earthquake forecasting have evaded scientists, even leading some to deem it intrinsically impossible to forecast them accurately. In this paper an attempt to forecast earthquakes and trends using a data of a series of past earthquakes. A type of recurrent neural network called Long Short-Term Memory (LSTM) is used to model the sequence of earthquakes. The trained model is then used to predict the future trend of earthquakes. An ordinary Feed Forward Neural Network (FFNN) solution for the same problem was done for comparison. The LSTM neural network was found to outperform the FFNN. The R^2 score of the LSTM is better than the FFNN’s by 59%.
Co-Authors R. Sivakumar S. Sridhar Snehasish Ghosh Tanvi Bhandarkar Vardaan K