A hybrid-forecasting model reducing Gaussian noise based on the Gaussian support vector regression machine and chaotic particle swarm optimization

Information Sciences

Volumn 238, Issue , 2013, Pages 96-110

  Wu, Qi ^a,b   Law, Rob ^b   Wu, Edmond ^c   Lin, Jinxing ^d  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c SUN YAT SEN UNIVERSITY   (China)

^d NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Chaotic mapping; Forecast; Gaussian loss function; Particle swarm optimization; Support vector regression machine

Indexed keywords

CHAOTIC MAPPING; CHAOTIC PARTICLE SWARM OPTIMIZATIONS; FORECAST; GAUSSIAN LOSS FUNCTIONS; GAUSSIANS; LOSS FUNCTIONS; REGRESSION ESTIMATES; SUPPORT VECTOR REGRESSION MACHINES;

FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); PARTICLE SWARM OPTIMIZATION (PSO); VECTORS;

REGRESSION ANALYSIS;

EID: 84876824801     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2013.02.017     Document Type: Article

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