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• W2089920493 abstract "This paper presents an artificial intelligence approach for optimization of the operational parameters such as gas pressure ratio and discharge current in a fast-axial-flow CW CO2 laser by coupling artificial neural networks and genetic algorithm. First, a series of experiments were used as the learning data for artificial neural networks. The best-trained network was connected to genetic algorithm as a fitness function to find the optimum parameters. After the optimization, the calculated laser power increases by 33% and the measured value increases by 21% in an experiment as compared to a non-optimized case." @default.
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• W2089920493 date "2008-11-01" @default.
• W2089920493 modified "2023-10-06" @default.
• W2089920493 title "Optimization of the operational parameters in a fast axial flow CW CO2 laser using artificial neural networks and genetic algorithms" @default.
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• W2089920493 doi "https://doi.org/10.1016/j.optlastec.2008.03.003" @default.
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