Artificial Intelligence Methods in Hydraulic System Design

被引：3
作者：
Filo, Grzegorz [1 ]
机构：
[1] Cracow Univ Technol, Fac Mech Engn, PL-31864 Krakow, Poland
来源：
ENERGIES | 2023年 / 16卷 / 08期
关键词：
hydraulic system design; artificial intelligence; artificial neural networks; evolutionary algorithms; fuzzy logic; NEURAL-NETWORK; RISK-ASSESSMENT; FLOW-CONTROL; VALVE; OPTIMIZATION; PERFORMANCE; DIAGNOSIS; MODEL;
D O I：
10.3390/en16083320
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
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.
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页数：19
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