@inproceedings{08e2ae3bfeef4a4d80550de94593b0b7,
title = "Deep Learning Multi-objective Optimization for Smart Manufacturing via Elitist Genetic Algorithm",
abstract = "This paper proposes a deep learning multi-objective optimization (DL-MOO) method for smart manufacturing to generate wire electrical discharge machining (WEDM) parameters via an elitist genetic algorithm with the deep neural network (DNN) and the transfer learning mechanism. Given multiple objectives, the proposed method can generate WEDM manufacturing parameters to optimize the multiple objectives at the same time. Practical experiments are conducted to validate the proposed method.",
keywords = "deep learning, elitist genetic algorithm, multi-objective optimization, smart manufacturing, transfer learning, wire electrical discharge machining",
author = "Jiang, {Jehn Ruey} and Chen, {Si Han}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 ; Conference date: 17-07-2023 Through 19-07-2023",
year = "2023",
doi = "10.1109/ICCE-Taiwan58799.2023.10226857",
language = "???core.languages.en_GB???",
series = "2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "545--546",
booktitle = "2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings",
}