Article ID Journal Published Year Pages File Type
739718 Optics & Laser Technology 2008 8 Pages PDF
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.

Related Topics
Physical Sciences and Engineering Engineering Electrical and Electronic Engineering
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