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基于遗传算法和文献可视化分析的智能体育场战略评估模型:以中国成都为例

Strategic assessment model of smart stadiums based on genetic algorithms and literature visualization analysis: A case study from Chengdu, China.

作者信息

Zhu Xi, Peng Xiaobo

机构信息

College of Physical Education, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.

School of Physical Education, Chengdu Normal University, Chengdu, 611130, Sichuan, China.

出版信息

Heliyon. 2024 May 22;10(11):e31759. doi: 10.1016/j.heliyon.2024.e31759. eCollection 2024 Jun 15.

Abstract

This paper leverages Citespace and VOSviewer software to perform a comprehensive bibliometric analysis on a corpus of 384 references related to smart sports venues, spanning from 1998 to 2022. The analysis encompasses various facets, including author network analysis, institutional network analysis, temporal mapping, keyword clustering, and co-citation network analysis. Moreover, this paper constructs a smart stadiums strategic assessment model (SSSAM) to compensate for confusion and aimlessness by genetic algorithms (GA). Our findings indicate an exponential growth in publications on smart sports venues year over year. Arizona State University emerges as the institution with the highest number of collaborative publications, Energy and Buildings becomes the publication with the most documents. While, Wang X stands out as the scholar with the most substantial contribution to the field. In scrutinizing the betweenness centrality indicators, a paradigm shift in research hotspots becomes evident-from intelligent software to the domains of the Internet of Things (IoT), intelligent services, and artificial intelligence (AI). The SSSAM model based on artificial neural networks (ANN) and GA algorithms also reached similar conclusions through a case study of the International University Sports Federation (FISU), building Information Modeling (BIM), cloud computing and artificial intelligence Internet of Things (AIoT) are expected to develop in the future. Three key themes developed over time. Finally, a comprehensive knowledge system with common references and future hot spots is proposed.

摘要

本文利用Citespace和VOSviewer软件,对1998年至2022年期间与智能体育场馆相关的384篇参考文献进行了全面的文献计量分析。该分析涵盖多个方面,包括作者网络分析、机构网络分析、时间映射、关键词聚类和共被引网络分析。此外,本文构建了智能体育场馆战略评估模型(SSSAM),以弥补遗传算法(GA)带来的混乱和盲目性。我们的研究结果表明,关于智能体育场馆的出版物数量逐年呈指数增长。亚利桑那州立大学是合作出版物数量最多的机构,《能源与建筑》是文献数量最多的出版物。同时,王X是该领域贡献最大的学者。在审视中介中心性指标时,研究热点的范式转变变得明显——从智能软件转向物联网(IoT)、智能服务和人工智能(AI)领域。基于人工神经网络(ANN)和GA算法的SSSAM模型通过对国际大学生体育联合会(FISU)的案例研究也得出了类似结论,建筑信息模型(BIM)、云计算和人工智能物联网(AIoT)有望在未来得到发展。随着时间的推移形成了三个关键主题。最后,提出了一个具有共同参考文献和未来热点的综合知识体系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bdb/11140808/8f00e1a3d6c5/gr1.jpg

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