| dc.description.abstract | In the fields of computer science and the environment, earthquake prediction is a common research challenge. As we are dealing with earthquakes, it is vital to build an effective earthquake system. Nowadays, deep learning and machine learning techniques are introduced to reduce the time and effort required from humans. Since the behavior of our data is similar to that of natural earthquakes, it is conceivable to use the same methodology to anticipate when they will occur. We have gone through various steps such as feature engineering, visualization, applying Artificial Neural Network, and Random Forest Regression.Here, Feature engineering is challenging and complex. Here, ANN achieved 92.42% accuracy and Random Forest Regression achieved a best fit score 87.49%. Thus we may draw the conclusion that combining seismic activity with machine learning and deep learning models sounds outstanding as it produces better results. | en_US |
