A Data-Driven Automatic Design Method for Electric Machines Based on Reinforcement Learning and Evolutionary Optimization
The design problems of electric machines are actually treated as a kind of mixed-integer problem, because the machine shapes are defined by some integer variables, such as number of slots, and the other variables, such as the tooth width, which are here called the fundamental and shape variables, re...
Hlavní autoři: | Takahiro Sato, Masafumi Fujita |
---|---|
Médium: | Článek |
Jazyk: | English |
Vydáno: |
IEEE
2021-01-01
|
Edice: | IEEE Access |
Témata: | |
On-line přístup: | https://ieeexplore.ieee.org/document/9427216/ |
Podobné jednotky
-
Estimating process‐based model parameters from species distribution data using the evolutionary algorithm CMA‐ES
Autor: Victor Van der Meersch, a další
Vydáno: (2023-07-01) -
Waveform design through the trade-off relationship between the MI criterion and the SINR criterion
Autor: Bin Wang, a další
Vydáno: (2024-12-01) -
Optimization of solder joints in embedded mechatronic systems via Kriging-assisted CMA-ES algorithm
Autor: Hamdani Hamid, a další
Vydáno: (2019-01-01) -
Evolutionary Reinforcement Learning: A Systematic Review and Future Directions
Autor: Yuanguo Lin, a další
Vydáno: (2025-03-01) -
Fault Diagnosis for Body-in-White Welding Robot Based on Multi-Layer Belief Rule Base
Autor: Bang-Cheng Zhang, a další
Vydáno: (2023-04-01)