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• W2787604567 abstract "Aiming at the problem that the production process of corundum refractory is complex and the product quality cannot be predicted effectively, a quality forecasting model based on support vector regression is proposed in this paper. Firstly, an effective data set is extracted according to corundum production characteristics. The least angle regression method is applied to select feature. Then linear combination method is used to obtain a customized kernel function for support vector regression model, where the model is optimized with cross-validation. The experimental results indicate the proposed model can predict corundum quality accurately and has good fitting ability and practicality." @default.
• W2787604567 created "2018-02-23" @default.
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• W2787604567 date "2017-06-01" @default.
• W2787604567 modified "2023-09-23" @default.
• W2787604567 title "Corundum production quality prediction based on support vector regression" @default.
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• W2787604567 doi "https://doi.org/10.1109/iciea.2017.8283171" @default.
• W2787604567 hasPublicationYear "2017" @default.
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