Affiliation:
1. Department of Software Engineering, Mus Alparslan University, Mus, Turkey
2. Department of Construction Technology, Mus Alparslan University, Mus, Turkey
Abstract
The aim of this study is to forecast the daily average temperature of Mus
province in Turkey using time series methods. The performance of three time
series forecasting models is compared: LSTM, PROPHET, and ARIMA. The
behavior of these models in temperature data is also investigated. It is
found that these methods give accurate results according to the MAE, MSE,
and RMSE error metrics. However, LSTM produces slightly better results. The
temperature data used in this study was obtained from the Mus Meteorology
Provincial Directorate. Accurate temperature forecasting is important for
many different areas, from energy, agriculture to water resource management.
This study is an important research step in temperature analysis and
forecasting, and it will contribute to relevant decision-making processes.
Publisher
National Library of Serbia
Subject
Renewable Energy, Sustainability and the Environment
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