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引用次数: 0
摘要
返回：P. K. Yadav、R. Bhasker、A. A. Stonier、G. Peter、A. Vijayakumar 和 V. Ganji：不同合同场景下基于机器学习的智能电网负荷预测。IET Generation, Transmission & Distribution 17, no. 8, 1918-1931 (2023)。https://doi.org/10.1049/gtd2.12828The 上述文章于 2023 年 3 月 27 日在线发表于 Wiley Online Library (wileyonlinelibrary.com)，经期刊主编 Christian Rehtanz 和 Federico Milano、工程与技术学会以及 John Wiley & Sons Ltd.同意，已被撤回。有人对该文章提出了质疑，包括出现了折磨人的短语，以及与以下文章的图片重复：L.Wang, S. Mao, B. M. Wilamowski and R. M. Nelms, "Ensemble Learning for Load Forecasting," in IEEE Transactions on Green Communications and Networking, 4, no. 2, pp.因此，我们无法保证文章内容的完整性和可靠性，决定撤回该文章。我们已通知作者，他们不同意撤稿。
RETRACTION: Machine learning based load prediction in smart-grid under different contract scenario
RETRACTION: P. K. Yadav, R. Bhasker, A. A. Stonier, G. Peter, A. Vijayakumar, and V. Ganji: Machine learning based load prediction in smart-grid under different contract scenario. IET Generation, Transmission & Distribution 17, no. 8, 1918-1931 (2023). https://doi.org/10.1049/gtd2.12828
The above article, published online on 27th March 2023 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Christian Rehtanz and Federico Milano; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.
Concerns were raised regarding the article, including the presence of tortured phrases, and duplication of images with the following article:
L. Wang, S. Mao, B. M. Wilamowski and R. M. Nelms, “Ensemble Learning for Load Forecasting,” in IEEE Transactions on Green Communications and Networking, 4, no. 2, pp. 616–628 (2020), https://doi.org/10.1109/TGCN.2020.2987304.
When the authors were contacted for an explanation, they did not address the concerns adequately. 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.
期刊介绍：
IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution. Practical papers in which examples of good present practice can be described and disseminated are particularly sought. Papers of high technical merit relying on mathematical arguments and computation will be considered, but authors are asked to relegate, as far as possible, the details of analysis to an appendix.
The scope of IET Generation, Transmission & Distribution includes the following:
Design of transmission and distribution systems
Operation and control of power generation
Power system management, planning and economics
Power system operation, protection and control
Power system measurement and modelling
Computer applications and computational intelligence in power flexible AC or DC transmission systems
Special Issues. Current Call for papers:
Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control - https://digital-library.theiet.org/files/IET_GTD_CFP_NGSPSMOC.pdf
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