کوپلینگ عامل پیش بینی درجه حرارت شبکه های عصبی و منطق فازی برای انجام مقررات آسایش حرارتی در یک ساختمان اداری

The main goal of this paper is to demonstrate the effectiveness of the hybrid neuro-fuzzy approach and the importance of efficiently designing the temperature forecast model, especially with respect to the selection of the order of the regressor for each of the external and internal parameters used. Therefore, a differential entropy-based method was applied in this study, which provided good forecasting performances for the NNARX model.