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Research on K-Means Clustering Algorithm Based on Improved Genetic Algorithm

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Big Data and Security (ICBDS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1415))

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Abstract

Genetic algorithm is the simulation of the natural biological evolution principle, through the selection, crossover, mutation three genetic operators to complete the evolution and inheritance of nature. The advantage of genetic algorithm is its strong ability of global optimization. However, genetic algorithm has premature phenomenon, which makes the algorithm produce sub optimal solution prematurely. In this paper, adaptive strategy is introduced. In the process of algorithm implementation, crossover probability and mutation probability are adjusted dynamically, and population evolution speed is automatically adjusted to ensure that the algorithm finally obtains the global optimal solution.

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Author information

Authors and Affiliations

  1. Ma’anshan University, Ma’anshan, China

    Lulu Zhang

  2. Anhui Business College, Anhui, China

    Yu Shu

Authors
  1. Lulu Zhang
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  2. Yu Shu
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Editor information

Editors and Affiliations

  1. Nanjing Institute of Technology, Nanjing, China

    Yuan Tian

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Tinghuai Ma

  3. King Saud Unviersity, Riyadh, Saudi Arabia

    Muhammad Khurram Khan

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© 2021 Springer Nature Singapore Pte Ltd.

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Zhang, L., Shu, Y. (2021). Research on K-Means Clustering Algorithm Based on Improved Genetic Algorithm. In: Tian, Y., Ma, T., Khan, M.K. (eds) Big Data and Security. ICBDS 2020. Communications in Computer and Information Science, vol 1415. Springer, Singapore. https://doi.org/10.1007/978-981-16-3150-4_46

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  • DOI: https://doi.org/10.1007/978-981-16-3150-4_46

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3149-8

  • Online ISBN: 978-981-16-3150-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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