انجمن علمی مهندسی و مدیریت پسماند ایران اکولوژی انسانی 3041-9255 5 14 2026 05 22 The planning of electricity: Forecasting using the ARMAX model consumed based and taking into account relative humidity The planning of electricity: Forecasting using the ARMAX model consumed based and taking into account relative humidity 245483 10.22034/he.2026.546827.1141 FA نعمه ساهون شنان جوذری گروه آمار، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران. محمد حسن بهزادی گروه آمار، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران. 0000-0002-1849-5588 محسن رستمی مال خلیفه گروه آمار، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران. Journal Article 2025 09 27 Effective energy demand forecasting in grid stability and resource management is essential especially in cases of extreme climate turmoil to various regions. The dilemma of large electricity consumption was discussed in Babylon, Iraq. In the climate of Babylon, the forecasting models seldom factor in the impact of relative humidity. Although earlier studies have addressed temperature, the impact of humidity on power load is not well studied in this region. In light of these conditions, it is imperative to apply an ARMAX model. To address this, from March to June 2024, an ARMAX (Automatic Moving Average with External Input) model was developed using daily relative humidity. The model was evaluated using AIC, BIC, and RMSE criteria. The least squares method was used to estimate the model parameters, the maximum likelihood method and RLS-KF method. Incorporation of humidity as external variable improves forecasting results considerably better than univariate models, results show. The findings provide practical insights for regional policymakers aimed at enhancing short-term energy planning and reducing resource allocation inefficiencies in climate sensitive regions. ARMAX model makes use of historic time series data as well as the influence of other variables in order to achieve greater accuracy in forecasting and understanding the causes of fluctuations in a greater detail. The need for intelligent forecasting tools is growing to tackle climate change, energy efficiency, economic impact, and more. Effective energy demand forecasting in grid stability and resource management is essential especially in cases of extreme climate turmoil to various regions. The dilemma of large electricity consumption was discussed in Babylon, Iraq. In the climate of Babylon, the forecasting models seldom factor in the impact of relative humidity. Although earlier studies have addressed temperature, the impact of humidity on power load is not well studied in this region. In light of these conditions, it is imperative to apply an ARMAX model. To address this, from March to June 2024, an ARMAX (Automatic Moving Average with External Input) model was developed using daily relative humidity. The model was evaluated using AIC, BIC, and RMSE criteria. The least squares method was used to estimate the model parameters, the maximum likelihood method and RLS-KF method. Incorporation of humidity as external variable improves forecasting results considerably better than univariate models, results show. The findings provide practical insights for regional policymakers aimed at enhancing short-term energy planning and reducing resource allocation inefficiencies in climate sensitive regions. ARMAX model makes use of historic time series data as well as the influence of other variables in order to achieve greater accuracy in forecasting and understanding the causes of fluctuations in a greater detail. The need for intelligent forecasting tools is growing to tackle climate change, energy efficiency, economic impact, and more.