遗传算法研究的结构与演化:科学计量学分析与可视化

Zhecheng Jing, H. Xue, Shupei Zhang, M. Wu
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引用次数: 0

摘要

遗传算法是一种利用自然选择和自然遗传机制的随机搜索算法。它被广泛应用于许多不同的学科。本文利用科学的测量分析系统对遗传算法的研究课题和现状进行了综述。研究了2010年至2019年Web of Science核心馆藏中的17551篇文章。引进国内最大的作者共引网络和最具影响力的期刊。确定了遗传算法研究涉及的学科和主题。建立了遗传算法知识结构的可视化网络。对引文进行了更深入的研究,探索相关研究的新兴领域和热点。本研究的结果为从业者提供了对遗传算法更好的理解,并有助于研究人员进行进一步的研究。
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Mapping the Structure and Evolution of Genetic Algorithm Research: A Scientometric Analysis and Visualization
Genetic algorithm is a kind of random search algorithm that draws on the natural selection and natural genetic mechanism. It is widely used in many different disciplines. This paper uses the scientific measurement analysis system to summarize the research topics and current status of genetic algorithms. 17551 articles from 2010 to 2019 were investigated from the Web of Science Core Collection. Introduced the largest author co-citation network and the most influential journals. The disciplines and topics involved in genetic algorithm research were identified. A visualization network of genetic algorithm knowledge structure is established. A more in-depth study of citations has been carried out to explore emerging areas and hotspots of related research. The results of this study provide practitioners with a better understanding of genetic algorithms and help researchers do further research.
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