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

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.