Load Forecasting Based on Genetic Algorithm–Artificial Neural Network-Adaptive Neuro-Fuzzy Inference Systems: A Case Study in Iraq

This study focuses on the important issue of predicting electricity load for efficient energy management. To achieve this goal, different statistical methods were compared, and results over time analyzed using various ratios layers training testing. uses an artificial neural network (ANN) model with advanced prediction techniques such as genetic algorithms (GA) adaptive neuro-fuzzy inference systems (ANFIS). article stands out a comprehensive compilation many features methodologies previously presented in other studies. long-term pattern process achieves lowest relative error values by hourly divided annual data testing training. Data samples applied to algorithms, we examined their effects predictions understand relationship between factors electrical load. shows that ANN–GA has good accuracy low rates compared models, resulting best performance our system.