摘要
近年来随着国内大型写字楼建筑的不断增多,能耗也迅速增长。为此,设计一个基于人工智能深度学习网络的写字楼能耗分析系统,首先对收集的能耗数据进行预处理,然后通过提取数据特征,运用反向传播网络对结果进行处理。该系统可通过训练大量能耗参数信息,评估写字楼历史能耗信息与当前能耗的量化关系,从而降低不必要的能耗,实现节能的目的。
In recent years,the number of large-scale office buildings in China has increased,and energy consumption has also in. creased rapidly. The energy consumption of electrical energy in buildings has also increased for 95% of the buildings are of high-ener. gy. This paper designs an office building energy consumption analysis system based on artificial intelligence deep learning network, pre-processes the collected energy consumption data,extracts data features,and uses the back propagation network to process the re. sults. The system can evaluate the quantitative relationship between the historical energy consumption information of the office building and the current energy consumption by training a large amount of energy consumption parameter information. Finally,the energy con. sumption evaluation results of the office building are divided into three categories:abnormal,normal,and waste.
作者
张珣
王雪永
ZHANG Xun;WANG Xue-yong(Institute of Modern Circuits and Intelligent Information,Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《软件导刊》
2019年第4期104-107,共4页
Software Guide
关键词
AI
能耗分析
写字楼
反向传播网络
深度学习网络
energy consumption analysis
office building
back propagation network
deep learning network
