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言語種別	英語
発行・発表の年月	2026/06
形態種別	学術論文
査読	査読あり
標題	Operational performance evaluation based on cloud-edge collaboration for the coking process
執筆形態	共著
掲載誌名	Control Engineering Practice
掲載区分	国外
出版社・発行元	Elsevier
巻・号・頁	171,pp.106857
総ページ数	11
担当範囲	Writing – review & editing, Formal analysis.
国際共著	国際共著
著者・共著者	Yi Ren, Xuzhi Lai, Jie Hu, Sheng Du, Luefeng Chen, Min Wu, Akinori Sekiguchi, Edwardo F. Fukushima
概要	The operational performance of the coking process reflects its energy utilization and production efficiency, and its evaluation is a prerequisite for achieving optimal operation. However, the coking process faces several challenges, including multi-source data integration, reliance on manual performance evaluation, and low efficiency in model deployment. To address these issues, this paper proposes an intelligent evaluation method for coking process operational performance, based on a practical cloud-edge collaborative framework. First, an improved temporal fusion transformer is developed to accurately predict comprehensive production indicators. Then, based on the prediction results, a performance indices system is constructed, and a dual-scale fuzzy performance evaluation mechanism is introduced to assess the operational performance. Finally, a cloud-edge deployment architecture is established, where the cloud layer is responsible for model training and updating, and the edge layer enables accurate prediction and evaluation. The proposed method is validated on real industrial data, demonstrating its effectiveness and accuracy, and providing strong support for subsequent optimization and control.
外部リンクURL	https://doi.org/10.1016/j.conengprac.2026.106857