收缩

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
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引用次数: 0

摘要

撤稿:S.S.M. Shah, S. Meganathan,“基于季风数据的智能城市电力消耗模型的机器学习方法”,《计算智能》第37期。3 (2021): 1309-1321, https://doi.org/10.1111/coin.12368.The上述文章于2020年7月9日在线发表在Wiley在线图书馆(wileyonlinelibrary.com)上,经主编Diana Inkpen同意撤回;和Wiley期刊有限责任公司。这篇文章是作为嘉宾编辑的一期的一部分发表的。经过出版商的调查,各方都得出结论,这篇文章被接受完全是基于一个妥协的同行评议过程。编辑们因此决定撤回这篇文章。作者已被告知撤稿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RETRACTION

RETRACTION: S.S.M. Shah, S. Meganathan, “ Machine Learning Approach for Power Consumption Model Based on Monsoon Data for Smart Cities Applications,” Computational Intelligence 37 no. 3 (2021): 13091321, https://doi.org/10.1111/coin.12368.

The above article, published online on 09 July 2020 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal Editor-in-Chief, Diana Inkpen; and Wiley Periodicals LLC. The article was published as part of a guest-edited issue. Following an investigation by the publisher, all parties have concluded that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors have been informed of the retraction.

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来源期刊
Computational Intelligence
Computational Intelligence 工程技术-计算机:人工智能
CiteScore
6.90
自引率
3.60%
发文量
65
审稿时长
>12 weeks
期刊介绍: This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.
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