Building neural network equipment models using model modifiertechniques |
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Authors: | Marwah M. Mahajan R.L. |
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Affiliation: | Dept. of Mech. Eng., Colorado Univ., Boulder, CO ; |
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Abstract: | In this paper, we address the problem of developing accurate neural network equipment models economically. To this end, we propose model modifier techniques in conjunction with physical-neural network models. Two model modifiers-difference method and source input method-are proposed and evaluated on a horizontal chemical vapor deposition reactor. The results show that the source input method outperforms the difference method. Further, to develop a model of comparable accuracy, the source input method reduces the number of experimental data points to approximately one fourth of those needed without this approach |
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