Mid-Long Term Load Forecasting Based on Fuzzy Soft Set and D-S Evidence Theory

Dong Xiao Niu; Lei Lei Fan; Qiao Ling Wu; Qing Guo Ma; Qin Liang Tan

doi:10.4028/www.scientific.net/AMR.732-733.682

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 732-733Mid-Long Term Load Forecasting Based on Fuzzy Soft...

Mid-Long Term Load Forecasting Based on Fuzzy Soft Set and D-S Evidence Theory

Abstract:

According to errors between the predicted values and the actual values, this paper establishes a fuzzy soft set in the form of membership function, then utilizes Dempster combination rule in evidence theory to synthesize the prediction results to obtain the weights of each single model, and thus builds a new hybrid combination forecasting model. The example shows that the proposed model can effectively improve the accuracy of mid-long term load forecasting, and is more accurate and credible than the combination forecasting model based on entropy or simply fuzzy soft set theory.

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Periodical:

Advanced Materials Research (Volumes 732-733)

Pages:

682-685

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.732-733.682

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Online since:

August 2013

Authors:

Dong Xiao Niu*, Lei Lei Fan, Qiao Ling Wu, Qing Guo Ma, Qin Liang Tan

Keywords:

Combination Forecasting, D-S Evidence Theory, Fuzzy Soft Set, Mid-Long Term

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