摘要：工业应用中电力供应链材料需求预测的新方法

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

摘要

引用本文：肖玉军，雷海红，A. Sharma， A. Sharma：一种新的电力供应链材料需求预测方法。IET协同智能制造第3期3,273 - 280（2021）。上述文章于2021年2月21日在Wiley在线图书馆（wileyonlinelibrary.com）上发表，经主编同意撤回；高亮，沈伟明；工程技术学会；约翰·威利&；这篇文章是作为特刊的一部分发表的。经过调查，IET, John Wiley &；Sons Ltd和该杂志已经确定，这篇文章没有按照该杂志的同行评议标准进行评议，有证据表明，特刊的同行评议过程受到了系统性的操纵。此外，大多数图缺少相关的单位和描述符，因此结果是不可理解的。因此，我们不能保证内容的完整性或可靠性，并已决定撤回该文章。作者已被告知，他们不同意撤稿。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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The above article, published online on 21 February 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.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