Indexed by:期刊论文
Date of Publication:2017-12-01
Journal:ENERGY AND BUILDINGS
Included Journals:Scopus、SCIE、EI
Volume:156
Page Number:78-84
ISSN No.:0378-7788
Key Words:Fuzzy theory; Information entropy; Sampling survey; Building energy consumption; Sample size
Abstract:The foundation of energy saving is knowing the real status of building energy consumption. For various kinds and a great number of building energy consumption data, the fuzzy theory is applied for sampling. It would make data representational. Firstly, a fuzzy clustering method is used to classify the data set and then the samples are extracted from the subclass. A modified clustering algorithm based on entropy weight method is proposed. It can determine the number of the classification of data set. The simulation results indicate that the new method can directly determine the optimal sample size. This method is suitably applied for dynamic energy consumption data and is more accurate compared with the statistical method. (C) 2017 Elsevier B.V. All rights reserved.
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