Evaluating the influence of generation methods on the quality of the smart designs of experiment
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This paper presents results of computer simulation made to evaluate how the quality of the smart designs of experiment depends on the methods of generating. The quality of smart designs was evaluated by comparing the known values of special testing functions simulating the real research object and approximated values predicted by neural networks trained with the sets based on smart designs of experiment. The results suggest the possibility of significant reducing the number of experiments runs using studied smart designs.
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