Forecasting of turbine heat rate with online least squares support vector machine based on gravitational search algorithm

Knowledge-Based Systems

Volumn 39, Issue , 2013, Pages 34-44

  Zhang, Weiping ^a,b   Niu, Peifeng ^a,c   Li, Guoqiang ^a,c   Li, Pengfei ^a,c  

^a YANSHAN UNIVERSITY   (China)

^b QINHUANGDAO INSTITUTE OF TECHNOLOGY   (China)

^c NATIONAL ENGINEERING RESEARCH CENTER FOR EQUIPMENT AND TECHNOLOGY OF COLD STRIP ROLLING   (China)

Author keywords

Gravitational search algorithm; Heat rate; Least squares support vector machine; Online learning; Steam turbine

Indexed keywords

ACTUAL SYSTEM; DYNAMIC PREDICTION; FORECASTING METHODS; GRAVITATIONAL SEARCH ALGORITHMS; HEAT RATE; KERNEL PARAMETER; LEAST SQUARE; LEAST SQUARES SUPPORT VECTOR MACHINES; OFFLINE DATA; ONLINE LEARNING; PARAMETER SELECTION; REGULARIZATION PARAMETERS; SAFE OPERATION;

ARTIFICIAL INTELLIGENCE; FORECASTING; LEARNING ALGORITHMS; STEAM TURBINES;

SUPPORT VECTOR MACHINES;

EID: 84871926704     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.10.004     Document Type: Article

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