An Iterative Modified Kernel Based on Training Data

ZHOU Zhi-xiang; HAN Feng-qing

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ZHOU Zhi-xiang, HAN Feng-qing. An Iterative Modified Kernel Based on Training Data[J]. Applied Mathematics and Mechanics, 2009, 30(1): 120-126.

Citation:

ZHOU Zhi-xiang, HAN Feng-qing. An Iterative Modified Kernel Based on Training Data[J]. Applied Mathematics and Mechanics, 2009, 30(1): 120-126.

Citation:

ZHOU Zhi-xiang, HAN Feng-qing. An Iterative Modified Kernel Based on Training Data[J]. Applied Mathematics and Mechanics, 2009, 30(1): 120-126.

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An Iterative Modified Kernel Based on Training Data

ZHOU Zhi-xiang¹,
HAN Feng-qing²

1.
College of Civil Engineering and Architecture, Chongqing Jiaotong University, Chongqing 400074, P. R. China;

Received Date: 2008-07-18
Rev Recd Date: 2008-12-03
Publish Date: 2009-01-15

Abstract

Abstract

In order to improve the performance of a support vector regression, a new method for modified kernel function is proposed. In this method the information of whole samples is included in kernel function by conformal mapping. So the kernel function is data-dependent. With random initial parameter of kernel function, the kernel function is modified repeatedly until a satisfactory effect is achieved. Compared with the conventional model, the improved approach needs not selecting parameters of kernel function. Simulation was finished for one-dimension continue function and strong earthquake event. The results show that the improved approach has better learning ability and forecasting precision than the traditional model. With the iteration number increasing, the figure of merit will decrease and converge. The speed of convergence depends on the parameters in the algorithm.
- support vector regression,
- data-dependent,
- kernel function,
- iteration

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References(12)

References

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