Multi-Step Prediction Algorithm for State Prediction Model

Abstract:

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Dynamic Bayesian networks can be well dealt with the time-varying multivariable problem. The state model based on Dynamic Bayesian networks can more accurately describe the relationship between the system state and the influencing factors. In this paper, the width of the reasoning is used to simplify the amount of data in the reasoning process. Multi-step state prediction is achieved by extending time-slice. Experiment has shown that the proposed algorithm can achieve better prediction results.

Info:

Periodical:

Advanced Materials Research (Volumes 143-144)

Edited by:

H. Wang, B.J. Zhang, X.Z. Liu, D.Z. Luo, S.B. Zhong

Pages:

634-638

DOI:

10.4028/www.scientific.net/AMR.143-144.634

Citation:

Z. L. Zhang and H. W. Song, "Multi-Step Prediction Algorithm for State Prediction Model", Advanced Materials Research, Vols. 143-144, pp. 634-638, 2011

Online since:

October 2010

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Price:

$35.00

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