Title of article :
Hybrid model based on SVM with Gaussian loss function and adaptive Gaussian PSO
Author/Authors :
Wu، نويسنده , , Qi and Wu، نويسنده , , Shuyan and Liu، نويسنده , , Jing، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
8
From page :
487
To page :
494
Abstract :
In view of the bad capability of the standard support vector machine (SVM) in field of white noise of input series, a new v-SVM with Gaussian loss function which is call g-SVM is put forward to handle white noises. To seek the unknown parameters of g-SVM, an adaptive normal Gaussian particle swarm optimization (ANPSO) is also proposed. The results of applications show that the hybrid forecasting model based on the g-SVM and ANPSO is feasible and effective, the comparison between the method proposed in this paper and other ones is also given which proves this method is better than v-SVM and other traditional methods.
Keywords :
particle swarm optimization , adaptive , Gaussian loss function , Forecasting , Support vector machine
Journal title :
Engineering Applications of Artificial Intelligence
Serial Year :
2010
Journal title :
Engineering Applications of Artificial Intelligence
Record number :
2125271
Link To Document :
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