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AI-Assisted Dynamic Modelling for Data Management in a Distributed System

Author

Listed:
  • Yingjun Wang

    (Guangdong Provincial Communication Group Co., Ltd., China)

  • Shaoyang He

    (CCCC Highway Consultants Co., Ltd., China)

  • Yiran Wang

    (Zhongwei Road and Bridge Equipment Jiangsu Co., Ltd., China)

Abstract

There are many interdependent computers available in distributed networks. In such schemes, overall ownership costs comprise facilities, such as computers, controls, etc.; buying hardware; and running expenses such as wages, electrical charges, etc. Strom use is a large part of operating expenses. AI-assisted dynamic modelling for data management (AI-DM) framework is proposed. The high percentage of power use is connected explicitly to inadequate planning of energy. This research suggests creating a multi-objective method to plan the preparation of multi-criteria software solutions for distributed systems using the fuzzy TOPSIS tool as a comprehensive guide to multi-criteria management. The execution results demonstrate that this strategy could then sacrifice requirements by weight.

Suggested Citation

  • Yingjun Wang & Shaoyang He & Yiran Wang, 2022. "AI-Assisted Dynamic Modelling for Data Management in a Distributed System," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(4), pages 1-18, October.
    • Handle: RePEc:igg:jisscm:v:15:y:2022:i:4:p:1-18
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    References listed on IDEAS

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    2. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
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