Hybrid Stacking Model for Earthquake Magnitude Prediction in Japan Using Time Series Data (1970-2024)

Nandhini P S, Malarvizhi V, Nekelash I L, Kanishkar B, Malliga S

2025

Abstract

Seismic prognosis is considered as one of the most important scientific challenges. Among many nations, Japan is in greatest need of such system due to the constant and frequent occurrence of strong earthquakes caused by tectonic activity in the Pacific seismic zone. Therefore, the development of an advanced early warning system is necessary to predict the earthquake in advance to prevent the disaster. For this purpose, data related to earthquakes are collected from 1970 to 2024. This time-series data is trained using the hybrid stacking model, based on Random Forest, Extra Trees and CatBoost as base models and Linear Regression as a meta-model. The objective of the proposed model is to enhance the precision of earthquake magnitude forecasting, focusing on significant earthquakes. The performance of the proposed model is evaluated using two parameters i.e. R-Squared and Mean Square Error (MSE). The dataset is split in to 80:20 ratio for training and testing data respectively. From the results, it is inferred that the developed hybrid model decreases error rates with an R-squared value of 0.83 and MSE of 0.066. Thus, the proposed work helps to improve early warning systems for earthquakes, minimizing risks in Japan.

Paper Citation

in Harvard Style

P S N., V M., I L N., B K. and S M. (2025). Hybrid Stacking Model for Earthquake Magnitude Prediction in Japan Using Time Series Data (1970-2024). In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 756-763. DOI: 10.5220/0013585200004664

in Bibtex Style

@conference{incoft25,
author={Nandhini P S and Malarvizhi V and Nekelash I L and Kanishkar B and Malliga S},
title={Hybrid Stacking Model for Earthquake Magnitude Prediction in Japan Using Time Series Data (1970-2024)},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={756-763},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013585200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Hybrid Stacking Model for Earthquake Magnitude Prediction in Japan Using Time Series Data (1970-2024)
SN - 978-989-758-763-4
AU - P S N.
AU - V M.
AU - I L N.
AU - B K.
AU - S M.
PY - 2025
SP - 756
EP - 763
DO - 10.5220/0013585200004664
PB - SciTePress