Research on Application of Sintering Basicity of Based on Various Intelligent Algorithms

Song Qiang, Zhang Hai-Feng

Abstract


Prediction of alkalinity in sintering process is difficult. Whether the level of the alkalinity of sintering process is successful or not is directly related to the quality of sinter. There is no good method, prediction of alkalinity by high complexity, the present nonlinear, strong coupling, high time delay, so the recent new technology, grey least square support vector machine have been introduced. In this paper, The weight of evaluation objectives has not given the corresponding consideration when solving the correlation degree by taking traditional grey relation analysis and it is with a lot of subjective factors, easily lead to mistakes in decision-making on program. What is more,a kind of alkaline grey support vector machine model, enables us to develop new formulations and algorithms to predict the alkalinity. In the model,


Keywords


basicity;in sintering process; grey relation analysis,grey least squares support vector machine; prediction; grey model

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DOI: http://doi.org/10.11591/ijeecs.v12.i11.pp7728-7737

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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