Retracted: Improvement and Optimization of Feature Selection Algorithm in Swarm Intelligence Algorithm Based on Complexity

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-01-24 DOI:10.1155/2024/9860175
Complexity
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引用次数: 0

Abstract

The presence of these indicators undermines our confidence in the integrity of the article’s content and we cannot, therefore, vouch for its reliability. Please note that this notice is intended solely to alert readers that the content of this article is unreliable. We have not investigated whether authors were aware of or involved in the systematic manipulation of the publication process.

In addition, our investigation has also shown that one or more of the following human-subject reporting requirements has not been met in this article: ethical approval by an Institutional Review Board (IRB) committee or equivalent, patient/participant consent to participate, and/or agreement to publish patient/participant details (where relevant).

Wiley and Hindawi regrets that the usual quality checks did not identify these issues before publication and have since put additional measures in place to safeguard research integrity.

We wish to credit our own Research Integrity and Research Publishing teams and anonymous and named external researchers and research integrity experts for contributing to this investigation.

The corresponding author, as the representative of all authors, has been given the opportunity to register their agreement or disagreement to this retraction. We have kept a record of any response received.

撤回:基于复杂性的蜂群智能算法中特征选择算法的改进与优化
这些指标的存在削弱了我们对文章内容完整性的信心,因此我们无法保证其可靠性。请注意,本通知仅用于提醒读者本文内容不可靠。此外,我们的调查还显示,本文不符合以下一项或多项人类受试者报告要求:机构审查委员会(IRB)或同等机构的伦理批准、患者/参与者同意参与和/或同意公布患者/参与者的详细信息(如相关)。Wiley和Hindawi感到遗憾的是,通常的质量检查未能在论文发表前发现这些问题,因此我们采取了更多措施来保护研究诚信。我们希望感谢我们自己的研究诚信团队和研究出版团队以及匿名和具名的外部研究人员和研究诚信专家为此次调查做出的贡献。我们已将收到的回复记录在案。
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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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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