{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:05:34Z","timestamp":1779289534012,"version":"3.51.4"},"reference-count":37,"publisher":"Emerald","issue":"4","funder":[{"name":"the key project of science and technology research program of Chongqing Education Commission of China","award":["KJZD-K202502103"],"award-info":[{"award-number":["KJZD-K202502103"]}]},{"name":"the Research Project on the Reform of Postgraduate Education and Teaching in Chongqing","award":["yjg223094"],"award-info":[{"award-number":["yjg223094"]}]},{"name":"the Chongqing Research Project of Higher Education Teaching Reform","award":["232077"],"award-info":[{"award-number":["232077"]}]},{"name":"Chongqing Natural Science Foundation of China","award":["CSTB2025NSCQ-MSX0459"],"award-info":[{"award-number":["CSTB2025NSCQ-MSX0459"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["72071023"],"award-info":[{"award-number":["72071023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,31]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To address the modeling challenge posed by complex systems that exhibit linearity, nonlinearity, local oscillations and long-term trends.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>The Euler polynomial, linear correction term and grey action quantity term are simultaneously introduced to extend the structure of the traditional multivariable grey prediction model. A variable-structure adaptive multivariable grey prediction model is then constructed. Furthermore, the model\u2019s performance is enhanced through the differential design and optimization of the accumulation orders for the dependent and independent variables, as well as the background value coefficients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>The proposed model is applied to simulate and predict the quarterly total electricity consumption in Guangzhou. The results show that the new model significantly outperforms several existing grey prediction models in terms of both accuracy and stability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>This study contributes to the further development and enrichment of multivariable grey prediction methodology, providing a novel approach for modeling complex systems characterized by local oscillations and long-term trends.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/gs-04-2025-0037","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T04:51:56Z","timestamp":1756961516000},"page":"792-815","source":"Crossref","is-referenced-by-count":1,"title":["Structural extension and parameter optimization of multivariable grey prediction model with real-number order and its 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