摘要
通过研究公共建筑耗能特点,结合建筑节能标准,提取了建筑能耗主要影响因素。在研究T-S模糊神经网络结构和算法的基础上,提出了基于T-S模糊神经网络的建筑能耗评估模型,用改进FCM聚类方法确定网络结构和参数初值,运用混合学习算法训练网络模型。将模型运用到评估实例中,结果表明基于改进FCM聚类的T-S模糊神经网络评估模型结构简单,学习和泛化能力强。
Main inflnence factors are extracted by analyzing characteristics of energy consumption with energy efficiency standards for building. The model for energy consumption assessment is built after researching structure and algorithm of TS fuzzy neural network. Improved FCM clustering is used to determine the structure of network and the initial values of former parameters. The model is trained by hybrid learning algorithm. The model is used to assess the energy consumption situation of public buildings. The structure of T-S fuzzy neural net- work assessment model based on improved FCM clustering is simple, and it has strong learning and generalization ability.
出处
《建筑节能》
CAS
2013年第11期67-69,共3页
BUILDING ENERGY EFFICIENCY
关键词
T-S模糊神经网络
改进FCM聚类
能耗评估模型
T-S fuzzy neural network
improved FCM clustering
assessment model of energy consumption
