Application of least squares support vector machines to predict the silicon content in blast furnace hot metal

ISIJ International

Volumn 48, Issue 11, 2008, Pages 1659-1661

  Jian, Ling ^a   Gao, Chuanhou ^b   Li, Lei ^a   Zeng, Jiusun ^b  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

^b ZHEJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BLAST FURNACES; CURVE FITTING; FEEDFORWARD NEURAL NETWORKS; FURNACES; GAS BURNERS; IMAGE RETRIEVAL; IRON; METAL REFINERIES; METALLURGICAL FURNACES; MULTILAYER NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; RESEARCH AIRCRAFT;

ACCURATE PREDICTIONS; BLAST FURNACE IRON MAKINGS; BLAST TEMPERATURES; COAL INJECTIONS; CROSS VALIDATIONS; HOT METALS; INPUT VARIABLES; IRON AND STEELS; KERNEL METHODS; LEAST SQUARE SUPPORT VECTOR MACHINES; LEAST SQUARES SUPPORT VECTOR MACHINES; LINE PREDICTIONS; MEAN SQUARES; OFF-LINE TESTS; ON-LINE APPLICATIONS; PREDICTIVE ACCURACIES; RADIAL BASIS FUNCTIONS; SILICON CONTENTS; SVM MODELS; THEORETICAL VALUES;

SUPPORT VECTOR MACHINES;

EID: 59649118425     PISSN: 09151559     EISSN: None     Source Type: Journal    
DOI: 10.2355/isijinternational.48.1659     Document Type: Article

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