一种径向基神经网络模型在图书馆能耗监测上的应用

摘要

At present, since most of the existing buildings have not installed energy consumption refined measuring equipment, developing reasonable and accurate energy-saving measures and realizing scientific management are difficult problems.The highest temperature、working time、humidity、solar radiation and the density of people are adopted to establish RBF model.It proves that the RBF network has a good fitting performance which provides reliable evidence for energy-saving measures and realizing scientific management.%由于大多数建筑没有安装能耗监测设备,如何合理、准确地制定节能措施以及实现科学化管理是一个比较困难的问题.针对这一问题,本文将日最高温度、工作时间、湿度、太阳辐射、人员密度作为影响图书馆能耗的主要因素,构建了基于径向基神经网络的能耗数据分析网络,并证明了径向基神经网络具有良好的拟合性能.为降低图书馆能耗的节能措施的制定和节能管理提供可靠依据.