TY - GEN
T1 - Time series analysis on earthquakes using EDA and machine learning
AU - Azis, Muhammad Fakhrillah Abdul
AU - Darari, Fariz
AU - Septyandy, Muhammad Rizqy
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/17
Y1 - 2020/10/17
N2 - An earthquake is a sudden, rapid shaking of the ground caused by the shifting of the Earth's tectonic plates. Earthquakes pose serious threats that cause economic losses and casualties. To mitigate such risks, it is crucial to better understand earthquakes through data-driven analysis. In this paper, we propose an approach to time series analysis over earthquake data, consisting of two steps: exploration and prediction. The exploration step relies on exploratory data analysis (EDA) comprising descriptive statistics and data visualization, whereas the prediction step focuses on how to predict the number of earthquakes for the following years. We perform our time series analysis using various machine learning techniques over a global earthquake dataset from 1965-2016 and report insights as well as lessons learned from the study.
AB - An earthquake is a sudden, rapid shaking of the ground caused by the shifting of the Earth's tectonic plates. Earthquakes pose serious threats that cause economic losses and casualties. To mitigate such risks, it is crucial to better understand earthquakes through data-driven analysis. In this paper, we propose an approach to time series analysis over earthquake data, consisting of two steps: exploration and prediction. The exploration step relies on exploratory data analysis (EDA) comprising descriptive statistics and data visualization, whereas the prediction step focuses on how to predict the number of earthquakes for the following years. We perform our time series analysis using various machine learning techniques over a global earthquake dataset from 1965-2016 and report insights as well as lessons learned from the study.
KW - Earthquake
KW - EDA
KW - Linear Regression
KW - LSTM
KW - Machine Learning
KW - Prophet
KW - Time Series Analysis
UR - http://www.scopus.com/inward/record.url?scp=85099750540&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS51025.2020.9263188
DO - 10.1109/ICACSIS51025.2020.9263188
M3 - Conference contribution
AN - SCOPUS:85099750540
T3 - 2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
SP - 405
EP - 412
BT - 2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
Y2 - 17 October 2020 through 18 October 2020
ER -