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Artificial Intelligence Methods in Hydraulic System Design

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  • Grzegorz Filo

    (Faculty of Mechanical Engineering, Cracow University of Technology, 31-864 Kraków, Poland)

Abstract

Reducing energy consumption and increasing operational efficiency are currently among the leading research topics in the design of hydraulic systems. In recent years, hydraulic system modeling and design techniques have rapidly expanded, especially using artificial intelligence methods. Due to the variety of algorithms, methods, and tools of artificial intelligence, it is possible to consider the prospects and directions of their further development. The analysis of the most recent publications allowed three leading technologies to be indicated, including artificial neural networks, evolutionary algorithms, and fuzzy logic. This article summarizes their current applications in the research, main advantages, and limitations, as well as expected directions for further development.

Suggested Citation

  • Grzegorz Filo, 2023. "Artificial Intelligence Methods in Hydraulic System Design," Energies, MDPI, vol. 16(8), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3320-:d:1118680
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    References listed on IDEAS

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    1. Maosen Xu & Guorui Zeng & Dazhuan Wu & Jiegang Mou & Jianfang Zhao & Shuihua Zheng & Bin Huang & Yun Ren, 2022. "Structural Optimization of Jet Fish Pump Design Based on a Multi-Objective Genetic Algorithm," Energies, MDPI, vol. 15(11), pages 1-16, June.
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    9. Stephen Ntiri Asomani & Jianping Yuan & Longyan Wang & Desmond Appiah & Kofi Asamoah Adu-Poku, 2020. "The Impact of Surrogate Models on the Multi-Objective Optimization of Pump-As-Turbine (PAT)," Energies, MDPI, vol. 13(9), pages 1-29, May.
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