科技广场Issue(9)：15-18,4.
基于小波神经网络的地铁车站内CO_2浓度预测控制
CO_2 Density Predication and Control of Subway Station Based on Wavelet Neural Network
王长涛 1王德宝2
作者信息
- 1. 沈阳建筑大学信息与控制工程学院,辽宁沈阳110168
- 2. 沈阳军区空军工程质量监督站,辽宁沈阳110015
- 折叠
摘要
Abstract
Wavelet function is in traduced into neural network prediction model is proposed to predict the carbon dioxide content of the subway platform as nonlinearity,time varying volatility and strong time delay.The Wavelet neural network system abstracts the advantages of wavelet analysis and traditional neural network,and has the capability of function learning and promoting for continuously absorbing environmental information as well.In this way,the carbon dioxide content which is disturbed by strong interference,time delay and uncertainty can be predicted accurately.关键词
小波神经网络/地铁站台/CO2含量/预测Key words
Wavelet/Subway Platform/Carbon Dioxide Content/Prediction分类
信息技术与安全科学引用本文复制引用
王长涛,王德宝..基于小波神经网络的地铁车站内CO_2浓度预测控制[J].科技广场,2011,(9):15-18,4.
