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An adaptive random experiment design method for engineering experiment

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Document pages: 23 pages

Abstract: This paper proposes an adaptive random experiment design (ARED) algorithmthat can be applied to optimize the multiple factors and levels experiments.The algorithm takes real-time model error as the adaptive condition, andoutputs a model that conforms to the error quantization standard based on theautomatic process. According to the actual experimental scenario, the similarnumber of test cases were selected between the ARED method and the comparativeexperimental design method under the bimodal Gaussian function, the bimodalsurface function and the peaks function, respectively. simultaneously, thesupport vector machine (SVM) algorithm is used to construct the model for theselected test cases, and the verification surface (or curve) is predicted. Thequalitative and quantitative analysis is carried out at two-slice ofapplicability and precision. The results show that the ARED method can beapplied to the experiment of multi-factor, and has better precision andapplicability than the comparative experimental methods.

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