Simulation and prediction of the alkalinity in sintering process based on grey least support vector machine

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Abstract Prediction of the alkalinity is a difficult problem during the process of sintering .Whether the level of he alkalinity of it is successful or not direct relates to the quality of sinter.By now,there isn��t a very good method due to the high complexity ,high non-linear, strong coupling, high delay-time and etc.A grey support vector machine model was proposed on the basis of the models.The fluctuation of data sequence is weakened by the grey theory and the support vector machine is capable of processing non-linear adaptable information, and the grey support vector machine is a combination of those advantages. The results reveal, the alkalinity of sinter can be accurately predicted through this model by reference to small sample and information. It was concluded that the grey support vector machine model is effective with the advantages of high precision, less samples required and simple calculation.

Key words�� alkalinity of sinter grey least support vector machine prediction the sintering process grey model.

Received: 02 June 2008

Corresponding Authors: SONG Qiang

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SONG Qiang. Simulation and prediction of the alkalinity in sintering process based on grey least support vector machine[J]. Chinese Journal of Iron and Steel, 2009, 16(5): 1-6.

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http://gt.chinamet.cn/Jweb_gtyjxb_en/EN/ OR http://gt.chinamet.cn/Jweb_gtyjxb_en/EN/Y2009/V16/I5/1