当前位置: X-MOL 学术Microprocess. Microsyst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Evaluation Method for Energy Saving Effect of Passive Ultra Low Energy Consumption Buildings based on Fuzzy Grey Clustering Method
Microprocessors and Microsystems ( IF 1.9 ) Pub Date : 2021-02-15 , DOI: 10.1016/j.micpro.2021.104097
Wei Xiong , Liangquan Hu

Due to the self factors of passive ultra-low energy consumption buildings, the evaluation accuracy of energy-saving effect is low. Therefore, based on the fuzzy grey clustering method, the energy-saving effect evaluation method of passive ultra-low-energy buildings is proposed. Firstly, the evaluation index weight of passive ultra-low energy consumption building energy-saving effect is determined by multi scheme decision-making method, and the index evaluation system is established according to the index weight, and the fuzzy similarity of evaluation indexes is calculated and clustered by fuzzy grey clustering method, so as to realize the passive ultra-low energy consumption building energy-saving effect evaluation. The experimental results show that the accuracy rate of this method is 98%, the evaluation rate is 96%, and the evaluation time is 540.54s. It is proved that the design method has high accuracy to evaluate the energy saving effect of passive ultra-low energy consumption building, and has certain feasibility.



中文翻译:

基于模糊灰色聚类的被动式超低能耗建筑节能效果评估方法

由于被动式超低能耗建筑的自身因素,节能效果的评估准确性较低。因此,基于模糊灰色聚类方法,提出了被动式超低能耗建筑的节能效果评价方法。首先,通过多方案决策方法确定被动式超低能耗建筑节能效果的评价指标权重,并根据指标权重建立指标评价体系,计算评价指标的模糊相似度。并通过模糊灰色聚类法进行聚类,从而实现了被动式超低能耗建筑节能效果评价。实验结果表明,该方法的准确率为98%,评价率为96%,评估时间为540.54s。实践证明,该设计方法对被动式超低能耗建筑的节能效果评估具有较高的准确性,具有一定的可行性。

更新日期:2021-02-15
down
wechat
bug