{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:36:18Z","timestamp":1775522178700,"version":"3.50.1"},"reference-count":32,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2017,8,7]],"date-time":"2017-08-07T00:00:00Z","timestamp":1502064000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2017,8,7]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>China is by far the world\u2019s largest energy consumer and importer. Reasonably forecasting the trend of China\u2019s total energy consumption (CTEC) is of great significance. The purpose of this paper is to propose a new-structure grey system model (NSGM (1, 1)) to forecast CTEC.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Two matrices for computing the parameters of NSGM (1, 1) were defined and the specific calculation formula was derived. Since the NSGM (1, 1) model increases the number of its background values, which improves the smoothness effect of the background value and weakens the effects of extreme values in the raw sequence on the model\u2019s performance; hence it has better simulation and prediction performances than traditional grey models. Finally, NSGM (1, 1) was used to forecast China\u2019s total energy consumption during 2016-2025. The forecast showed CTEC will grow rapidly in the next ten years.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Therefore, in order to meet the target of keeping CTEC under control at 4.8 billion tons of standard coal in 2020, Chinese government needs to take necessary measures such as transforming the economic development pattern and enhancing the energy utilization efficiency.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>A new-structure grey forecasting model, NSGM (1, 1), is proposed in this paper, which improves the smoothness and weakens the effects of extreme values and has a better structure and performance than those of other grey models. The authors successfully employ the new model to simulate and forecast CTEC. The research findings could aid Chinese government in formulating energy policies and help energy exporters make rational energy yield plans.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-05-2017-0011","type":"journal-article","created":{"date-parts":[[2017,6,27]],"date-time":"2017-06-27T07:32:43Z","timestamp":1498548763000},"page":"194-217","source":"Crossref","is-referenced-by-count":20,"title":["Forecasting the total energy consumption in China using a new-structure grey system model"],"prefix":"10.1108","volume":"7","author":[{"given":"Bo","family":"Zeng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengming","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020120602241296700_ref001","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.rser.2014.01.069","article-title":"A review on applications of ANN and SVM for 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