E3S Web Conf.
Volume 118, 20192019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|Number of page(s)||5|
|Section||Environmental Protection, Pollution and Treatment|
|Published online||04 October 2019|
Research On Public Building Energy Consumption Prediction Method Based On NAR Neural Network Prediction Technology
College of electrical and information engineering, Lanzhou university of technology, Lanzhou, Gansu, China
2 Key laboratory0 of advanced industrial process control in Gansu province
3 Lanzhou university of technology electrical and control engineering national experimental teaching demonstration center
In order to solve the problem of high energy consumption of public buildings and optimize and improve energy conservation of public buildings, we built a building energy consumption prediction model based on NAR neural network prediction technology improved by BP neural network algorithm, and the energy consumption value is predicted. The large public buildings as the research object, the key factors to determine the effect of building energy consumption and collect the corresponding data processing, as the input parameters of neural network prediction public buildings energy consumption value, according to the actual situation will eventually NAR prediction of neural network and BP network prediction method and the comparative analysis the measured data. The results show that NAR neural network can predict the energy consumption of public buildings more accurately than BP neural network under different building parameters.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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