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Proceedings of

2nd International Conference on Advances In Civil, Structural and Environmental Engineering ACSEE 2014

"APPLYING ARTIFICIAL NEURAL NETWORKS TO ESTIMATE THE ENERGY PERFORMANCE OF BUILDINGS"

DANIEL LEPADATU
DOI
10.15224/978-1-63248-030-9-55
Pages
267 - 272
Authors
1
ISBN
978-1-63248-030-9

Abstract: “The main objective of this study is to present a more accurate method to estimate the energy performance of buildings. This purpose is meant to evaluate the feasibility and relevance of more complex statistical modeling techniques, such as the artificial neural network. The energy performance of buildings may be estimated by their capacity to ensure a healthy and comfortable environment, with low energy consumption during the whole year. The glazed areas have a decisive role in the building energy performance having in view the complex functions that they play in the system. A parametric study, based on another powerful tool - the design of experiment method, which allows us to emphasize the measure in which the geometric and energetic characteristics of glazed areas influence the energy efficiency, estimated by the yearly energy needs, to ensure a comfortable and healthy environment. An artificial neural network - ANN is a computational model inspired by the biological natural neuron.”

Keywords: buildings energy, artificial neural networks, design of experiment method

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