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Energy Consumption Prediction of Residential Buildings Using Fuzzy Neural Networks

  • Sanan Abizada
  • Esmira AbiyevaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 896)

Abstract

This paper presents an energy consumption prediction model of residential buildings using fuzzy neural networks (FNN). The design of FNN prediction model has been performed using clustering and gradient descent algorithms. A cross-validation procedure is used for the training of the FNN. The descriptions of the training algorithms have been given. The statistical data is applied to design FNN. The obtained simulation results prove the effectiveness of using FNN in the energy consumption prediction of residential buildings. Based on prediction results of the energy consumption, the efficient ventilation system of the buildings can be planned. As a result, the energy waste can be decreased considerably.

Keywords

Energy consumption Fuzzy neural networks Prediction 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Electrical and Electronic Engineering DepartmentNear East UniversityNicosiaTurkey
  2. 2.Economics DepartmentNear East UniversityNicosiaTurkey

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