@article{e7b0d27858574879a93d38832a2bd74b, title = "Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings", abstract = "Benchmarking systems from a sample of reference buildings need to be developed to conduct benchmarking processes for the energy efficiency of commercial buildings. However, not all benchmarking systems can be adopted by public users (i.e., other non-reference building owners) because of the different methods in developing such systems.An approach for benchmarking the energy efficiency of commercial buildings using statistical regression analysis to normalize other factors, such as management performance, was developed in a previous work. However, the field data given by experts can be regarded as a distribution of possibility. Thus, the previous work may not be adequate to handle such fuzzy input-output data. Consequently, a number of fuzzy structures cannot be fully captured by statistical regression analysis. This present paper proposes the use of fuzzy linear regression analysis to develop a benchmarking process, the resulting model of which can be used by public users. An illustrative example is given as well. {\textcopyright} 2012 Elsevier Ltd.", keywords = "Benchmarking method, Building energy efficiency, Fuzzy linear regression method", author = "William Chung", year = "2012", month = jul, doi = "10.1016/j.apenergy.2012.01.061", language = "English", volume = "95", pages = "45--49", journal = "Applied Energy", issn = "0306-2619", publisher = "ELSEVIER SCI LTD", }