Using machine learning algorithms to predict the maximum electric energy demand
نویسندگان :
علیرضا چاجی ( Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dasht-e Azadegan, Khuzestan, Iran ) , Jalal Chachi ( Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Iran. Abstract: )
چکیده
This paper aims to predict the maximum electric energy demand that is helpful to ease the appropriate arrangement of effective situations (such as the scheduling of eliminating some consumers). In this study there are 24 features the backward forward and stepwise regressions are applied to find the significant features for a reduced model. The two algorithms (neural network and regression) are applied on the training set (60 percentage) of the real data then tested with the test set data (40 percentage). The results show that both proposed models can be useful but the regression model performs better than the neural network model to predict the next day’s maximum demand of the electric energy.کليدواژه ها
machine learning feature regression neural networkکد مقاله / لینک ثابت به این مقاله
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در صورتی که می خواهید در اثر پژوهشی خود به این مقاله ارجاع دهید، به سادگی می توانید از عبارت زیر در بخش منابع و مراجع استفاده نمایید:علیرضا چاجی , 1400 , Using machine learning algorithms to predict the maximum electric energy demand , اولین کنفرانس بین المللی ریاضیات و کاربردها
