基于BP神经网络模型的地铁通风空调系统负荷预测方法分析  

Analysis of Load Forecasting Method of Subway Ventilation and Air Conditioning System Based on BP Neural Network Model

作　　者：高晓辉 GAO Xiao-hui(Dongying People's Hospital,Dongying257091,China)

机构地区：[1]东营市人民医院,山东东营257091

出　　处：《工程建设与设计》2023年第16期45-47,共3页Construction & Design for Engineering

摘　　要：以地铁通风空调系统为例,分析了基于BP神经网络模型的负荷预测模型在节能方案中的实施要点,通过收集、筛选与整理历史数据,加强预处理数据,结合实际建模,实施BP神经网络模型优化,预测了地铁通风空调系统的负荷。结论表明,建筑工程节能施工方案应以节能需求为导向,本项目的运行空调通风性能达到了预期目标。Taking the subway ventilation and air conditioning system as an example,this paper analyzes the implementation key points ofthe load prediction model based on BP neural network model in the energy-saving scheme.By cllcting,screening and sorting out historical data,strengthening pre-processing data,combined with practical modeling,implementing BP neural network model optimization,the load of subway ventilation and air conditioning system is predicted.The conclusion shows that the energy-saving construction scheme of building should be guidedby energy-saving demand,andthe air conditioning and ventilation per formance ofthis projectcanreach the expected goal.

关 键 词：建筑环境与设备工程 地铁通风空调系统 节能施工 

分 类 号：TU962[建筑科学]