The Improved Markov Error Correcting Method in Gray SVM for Power Load Forecasting

As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey SVM can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov c...

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Bibliographic Details
Main Authors: Dongxiao Niu, Jialiang Lv, Xingzhi Zhang
Format: Conference Proceeding
Language:English
Subjects:
Computer errors
Error correction
Information technology
Load forecasting
markov chain
Optimization methods
Power load
Predictive models
Stochastic systems
Support vector machines
SVM algorithm
Technology forecasting
Testing
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Summary:As the power load forecasting sequence has stochastic growth and nonlinear wave characteristics, grey SVM can effective reflect the growth properties of the sequence and fit the nonlinear relation. Markov chain can easily embody the random characteristic of system by complex factors, so the Markov chain error correction method was introduce in this paper, the whole forecasting precision of the sequence was optimized, and the transfer matrix for the forecasting sequence was decided, then the accuracy for power load forecasting was greatly improved. Through the demonstration test, the precision is better than ingenuous grey SVM, the method in this paper have feasibility in practice.
DOI:10.1109/IITA.Workshops.2008.88