• RAVI SHARMA
• A.J. Singh

In these days Artificial Intelligence plays a very important role in our life. Deep Learning is one of the topics in which researchers and academician taking an interest. Computer Vision, Natural Language Processing are some of the applications where deep learning performance is very remarkable. There is a different type of models in Deep Learning Autoencoder, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), etc. CNN models are best suited for Image classification problem and RNN model is for Time Series Data. Earthquake prediction is a challenging task because there is no state-of-the-art method to solve this problem. In this research, we use Long Short-Term Memory (LSTM) a type of RNN model to predict earthquake and we will find significant improvement from the existing approach

Deep Learning, CNN, RNN, LSTM, Earthquake Prediction.

"Performance Evaluation of LSTM Model for Earthquake Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.777-780, June-2019, Available :http://www.jetir.org/papers/JETIR1906889.pdf

"Performance Evaluation of LSTM Model for Earthquake Prediction ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp777-780, June-2019, Available at : http://www.jetir.org/papers/JETIR1906889.pdf