RETRACTION: A novel method of material demand forecasting for power supply chains in industrial applications

IF 2.5 Q2 ENGINEERING, INDUSTRIAL

IET Collaborative Intelligent Manufacturing Pub Date : 2024-11-28 DOI:10.1049/cim2.70012

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引用次数: 0

Abstract

RETRACTION: Y. Xiao, Z. Jun, H. Lei, A. Sharma, A. Sharma: A novel method of material demand forecasting for power supply chains in industrial applications. IET Collaborative Intelligent Manufacturing 3, no. 3, 273–280 (2021). https://doi.org/10.1049/cim2.12007.

The above article, published online on 21 February 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.

This article was published as part of a guest-edited special issue. Following an investigation, the IET, John Wiley & Sons Ltd and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. In addition, most graphs are missing relevant units and descriptors so that the results are not comprehensible. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed and they disagree with the retraction.

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来源期刊

IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering

CiteScore

9.10

自引率

2.40%

发文量

审稿时长

20 weeks

期刊介绍： IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).