{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T19:04:07Z","timestamp":1754161447413,"version":"3.41.2"},"reference-count":14,"publisher":"Emerald","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,10,28]]},"abstract":"<jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>\u2013 The purpose of this paper is to analyse the results of energy audit reports and defines most favourable characteristics of system, which is energy consumption of buildings, and most favourable factors affecting these characteristics in order to modify and improve them.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design\/methodology\/approach<\/jats:title>\n                  <jats:p>\u2013 Grey set theory has the advantage of using fewer data to analyse many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which requires massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyse energy consumption in buildings of the Oil Ministry in Tehran. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named \u201cno standard deviation\u201d, \u201clow standard deviation\u201d and \u201cnon-standard\u201d. Entropy of coefficient vector of grey evaluations is calculated to investigate greyness of results.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>\u2013 According to the results of the model, \u201cthe real building load coefficient\u201d has been selected as the most important system characteristic and \u201cuncontrolled area of the building\u201d has been diagnosed as the most favourable factor which has the greatest effect on energy consumption of building.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Research limitations\/implications<\/jats:title>\n                  <jats:p>\u2013 Clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66 per cent.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Practical implications<\/jats:title>\n                  <jats:p>\u2013 It shows that among the 38 buildings surveyed in terms of energy consumption, three cases are in standard group, 24 cases are in \u201clow standard deviation\u201d group and 11 buildings are completely non-standard.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Originality\/value<\/jats:title>\n                  <jats:p>\u2013 In this research, a comprehensive analysis of the audit reports is proposed. This analysis helps the improvement of future audits, and assists in making energy conservation policies by studying the behaviour of system characteristic and related factors.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1108\/gs-01-2014-0002","type":"journal-article","created":{"date-parts":[[2014,11,5]],"date-time":"2014-11-05T08:26:27Z","timestamp":1415175987000},"page":"386-399","source":"Crossref","is-referenced-by-count":6,"title":["Analyzing the results of buildings energy audit by using grey incidence analysis"],"prefix":"10.1108","volume":"4","author":[{"given":"Tooraj","family":"Karimi","sequence":"first","affiliation":[{"name":"Faculty of Production Management, University of Tehran, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey","family":"Forrest","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Slippery Rock University, Slippery Rock, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"2025072817544845900_b1","doi-asserted-by":"crossref","unstructured":"Da-fang, L.\n           and Qing-chun, W. 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