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In this paper, the use of Adaptive Neural-Fuzzy Inference System (ANFIS) to study the design of Short-Term Load Forecasting (STLF) systems for the east of Iran was explored. This paper forecasts consumed load by using multi ANFIS. Entries of the presented model are into the multi ANFIS including the date of the day, temperature maximum and minimum, climate condition and the previous days consumed...
The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques to solve different engineering problems. Besides, Short Term Electrical Load Forecasting (STLF) is one of the important concerns of power systems and accurate load forecasting is vital for managing supply and demand of electricity. This study estimates short term electricity loads...
This paper compares two expert models in daily stream flow forecasting. The adaptive-neuro fuzzy inference system (ANFIS) model, artificial neural networks with radial base function (RBF) are used to forecast daily river flow in northwest of Iran and the results of these models are compared with Observed daily values. Daily river flow data in Mahabad-Dam station on Mahabad river in northwest of Iran...
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