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The Development and Innovation of Financial Enterprises Based on Artificial Fish Swarm Algorithm

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2020 International Conference on Applications and Techniques in Cyber Intelligence (ATCI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1244))

Abstract

By constructing projection index function to optimize the design, a projection pursuit comprehensive evaluation model (AFSA-PP) based on artificial fish swarm algorithm is established to evaluate the development and innovation of financial enterprises. The results show that the interpolation of development and innovation has a good adaptability for the comprehensive evaluation model, and it is in the same accuracy, compared with raga-pp evaluation model, AFSA-PP needs shorter optimization time and is more suitable for the rapid evaluation of innovation in modern financial enterprises.

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Acknowledgements

The Research Project of Philosophy and Social Science in Colleges and Universities of Shanxi Province (2019W205).

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Authors and Affiliations

  1. Lüliang University, Lüliang, 033000, China

    Shanshan Feng

Authors
  1. Shanshan Feng
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Corresponding author

Correspondence to Shanshan Feng .

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Editors and Affiliations

  1. Distributed System and Security Research Cluster, Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. Shanghai University of Medicine and Health Sciences, Shanghai, China

    Zheng Xu

  4. University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

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Feng, S. (2021). The Development and Innovation of Financial Enterprises Based on Artificial Fish Swarm Algorithm. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_157

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