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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 58
Paper Published : 1075
No. of Authors : 2871
  Journal Paper


Paper Title :
Building Energy Modeling using Non-Linear Auto Regression Neural Networks

Author :Nabil Nassif

Article Citation :Nabil Nassif , (2019 ) " Building Energy Modeling using Non-Linear Auto Regression Neural Networks " , International Journal of Advances in Mechanical and Civil Engineering (IJAMCE) , pp. 88-91 , Volume-6,Issue-5

Abstract : The paper discusses the modeling methodologies for building energy system using non-linear auto regression artificial neural networks. The model predicts whole building energy consumptions as a function of four input variables, dry bulb and wet bulb outdoor air temperatures, hour of day and type of day. To train and test the models, data from two existing buildings and from simulations are collected and used. The data are pre-processing using wavelet basis to remove the noise and anomalies. Different neural network structures are then tested along with various input delays to determine the one yielding the best results. The results show that the model can predict the energy consumptions accurately and it can be then used for various energy efficiency and saving estimation applications. Keywords - Building Energy Model, Neural Network, Wavelet Transfer, HVAC System, Regression Model.

Type : Research paper

Published : Volume-6,Issue-5


DOIONLINE NO - IJAMCE-IRAJ-DOIONLINE-16319   View Here

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