| Issue |
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|
|
|---|---|---|
| Article Number | 05017 | |
| Number of page(s) | 11 | |
| Section | Machine Learning & Neural Networks | |
| DOI | https://doi.org/10.1051/itmconf/20235605017 | |
| Published online | 09 August 2023 | |
Earthquake prognosis using machine learning
Department of Engineering Sciences and Humanities, Vishwakarma Institute of Technology, Pune, Maharashtra, India
* Corresponding Author: sachin.sawant@vit.edu
* purva.golegaonkar22@vit.edu
One of the deadliest and riskiest natural disasters is an earthquake. They often occur without a warning or any further alert. Therefore there was a need for its prognosis as it is extremely important for mankind as well as the environment. In this project, the successful application of machine learning techniques have been used for different elements of research which would be possible to use to make a more accurate short-term prognosis of upcoming earthquakes. Random Forest Classifier is the algorithm used for the research.
Key words: Earthquake / Random Forest / Machine Learning / Latitude / Longitude
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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