Long period power load forecasting is for 1–5 years time. It is significant to the reasonable planning and construction of power system. The present rough set theory developed mathematical approach is not fine, because the decision attribute is not defined elaborate. On the basis of practical examples of one area data, this paper promotes a newly attribute find method. The analysis of the calculation examples shows that it is feasible to forecast the power load under the effect of data uncertainty by rough set theory. Thus it can be seen this method will put to use in other fields, such as traffic transportation as well as logistics load forecast. For the sake of that this tool is simple and the data is available.


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    Titel :

    Electric Load Forecasting Method Based on Theory of Rough Set in Decomposed Decision Attribute


    Beteiligte:
    Yang, Yong (Autor:in) / Pu, Yun (Autor:in)

    Kongress:

    First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    2007-07-09




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Electric Load Forecasting Method Based on Theory of Rough Set in Decomposed Decision Attribute

    Yang, Y. / Pu, Y. / China Communications and Transportation Association; Transportation & Development Institute (American Society of Civil Engineers) | British Library Conference Proceedings | 2007




    Sequentially decomposed programming

    Nelson, II, Sigurd / Papalambros, Panos | AIAA | 1996


    Sequentially Decomposed Programming

    Nelson, S. / Papalambros, P. / American Institute of Aeronautics and Astronautics et al. | British Library Conference Proceedings | 1996