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All Journal Riwayat: Educational Journal of History and Humanities
Tannuru Marthamurtadh
Bina Nusantara University
Humanities Education Social Sciences

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Ozone Gases Value Forecasting Using Encoder-Decoder LSTM Model Ni Ketut Intan Rahayu*; Devi Fitrianah; Elvin Elvin; Tannuru Marthamurtadh
Riwayat: Educational Journal of History and Humanities Vol 6, No 3 (2023): Social, Political, and Economic History
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v6i3.34435

Abstract

Climate change, as one of the impacts of global warming, has several consequences for the sustainability of living beings on Earth. It is necessary to monitor the trend of climate change. One way to monitor seasonal patterns of change is by analyzing the ozone content in the air. In addition to being an indicator of climate change, predicting the ozone gas content in the air is important because ozone gas has a direct impact on living organisms. By predicting the ozone gas content, it is hoped that preventive measures can be taken to prevent the adverse effects of ozone gas in the air. In the case of predicting ozone gases, there may be certain patterns that only become apparent over time, such as seasonal variations or long-term trends. A model that can capture these long-term dependencies will be better equipped to accurately predict ozone gas levels in the future. In this experiment, we proposed the use of Encoder-Decoder LSTM to predict ozone gas values.
Co-Authors Devi Fitrianah Elvin Elvin Ni Ketut Intan Rahayu*