TY - JOUR
TI - Analysis and forecasting of temperature using time series forecasting methods a case study of Mus
AU - Tugal Ihsan
AU - Sevgin Fatih
JN - Thermal Science
PY - 2023
VL - 27
IS - 4
SP - 3081
EP - 3088
PT - Article
AB - 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.