An ensemble ELM based on modified AdaBoost.RT algorithm for predicting the temperature of molten steel in ladle furnace

IEEE Transactions on Automation Science and Engineering

Volumn 7, Issue 1, 2010, Pages 73-80

  Tian, Hui Xin ^a   Mao, Zhi Zhong ^a  

^a NORTHEASTERN UNIVERSITY   (China)

Author keywords

AdaBoost.RT; Ensemble algorithm; Extreme learning machine (ELM); Ladle furnace; Self adaptive

Indexed keywords

ARTIFICIAL INTELLIGENT; BP NETWORKS; ENSEMBLE ALGORITHMS; EXTREME LEARNING MACHINE; GENERALIZATION PERFORMANCE; HYBRID INTELLIGENCE; INDUSTRIAL PROCESSS; INDUSTRIAL PRODUCTION; INTELLIGENT ALGORITHMS; INTELLIGENT METHOD; INTELLIGENT MODELS; INTELLIGENT PREDICTION; IRON AND STEEL; LADLE FURNACES; METALLURGIC PROCESS; MOLTEN STEEL; PRODUCTION DATA; REGRESSION PROBLEM; SELF-ADAPTIVE; TEMPERATURE PREDICTION;

ARTIFICIAL INTELLIGENCE; FURNACES; IRON; LADLES; LEARNING SYSTEMS; MARTENSITIC STAINLESS STEEL; MATHEMATICAL MODELS; STEEL FOUNDRY PRACTICE;

LEARNING ALGORITHMS;

EID: 73849104985     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2008.2005640     Document Type: Article

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