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- W2350397580 abstract "To improve mid-term load-forecasting accuracy, using Minimax Probability Machine Regression (MPMR), a brand-new technology,is proposed. The regression function maximizes the minimum probability that future predication will be within aneto the true regressionfunction. With competition data from EUNITE Network, the model for load forecasting is built after analyzing data, and the experiment ofchoosing different train samples is done with good results. The experimental results with other methods are compared and some explanationsare presented. Kernel function shape parameter and regression tube value will influence the MPMR-based system performance. In experiments,cross validation to choose the two parameters is used. In the end of the paper, the features of MPMR, comparing with other methods, such asthe Relevance Vector Machine, etc. are summarized." @default.
- W2350397580 created "2016-06-24" @default.
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- W2350397580 date "2004-01-01" @default.
- W2350397580 modified "2023-09-23" @default.
- W2350397580 title "Mid-term load forecasting with MPMR" @default.
- W2350397580 hasPublicationYear "2004" @default.
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