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Abstract
ABSTRACTThe identification of appropriate reaction models is very helpful for developing chemical vapor deposition (CVD) processes. In this paper we propose a novel system to analyze experimental data of various CVD reactors and identify reaction models automatically using Genetic Algorithms (GA) with multiple process simulators and modeled functions. We demonstrate that this system is able to adequately model reaction systems, and that complex analysis of various experimental data increased the reliability of the reaction modeling results.
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