Abstract
Seismic tremors are among the foremost perilous normal fiascos individuals confront due to their event without earlier caution and their effect on their lives and properties. In expansion, to consider future disaster prevention measures for major earthquakes, it is necessary to predict earthquakes using Neural Networks (NN). A machine learning technique has developed a technology to predict earthquakes from ground controller data by measuring ground vibration and transmitting data by a sensor network. Devices to process this data and record it in a catalog of seismic data from 1900-2019 for Iraq and neighboring regions, then divide this data into 80% training data and 20% test data. It gave better results than other prediction algorithms, where the NN model performs better Seismic prediction than other machine learning methods.
Author supplied keywords
Cite
CITATION STYLE
Jarah, N. B., Alasadi, A. H. H., & Hashim, K. M. (2024). A New Algorithm for Earthquake Prediction Using Machine Learning Methods. Journal of Computer Science, 20(2), 150–156. https://doi.org/10.3844/jcssp.2024.150.156
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.