Prediction of Heating Energy Consumption in Houses via Deep Learning Neural Network

الموضوعات : Analytical and Numerical Methods in Mechanical Design

Newsha Valadbeygi ¹ , Ali Shahrjerdi ²

1 - Faculty of Mechanical Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran
2 - Faculty of Mechanical Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran

تاريخ الإرسال : 16 الأربعاء , ربيع الأول, 1444 تاريخ التأكيد : 16 الأربعاء , ربيع الأول, 1444 تاريخ الإصدار : 07 الخميس , جمادى الأولى, 1444

الکلمات المفتاحية: Neural network, heat transfer, energy consumption, deep learning,

ملخص المقالة :

This paper presents a novel model for prediction of energy consumption and heat transfer in houses on the basis of neural network by the use of experimental dataset of some cities of Iran for the learning process. To this end, a deep learning neural network (DNN) is designed by means of real set of data as input. In order to evaluate the proposed network, the predicted results are compared with the results obtained from the practical schemes. The comparison approved the effectiveness and feasibility of the suggested network in prediction of energy consumption and heat transfer with a low error for regression.

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