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RS-SVM forecasting model and power supply-demand forecast

✍ Scribed by Yang, Shu-xia ;Cao, Yuan ;Liu, Da ;Huang, Chen-feng

Book ID
107507770
Publisher
Chinese Electronic Periodical Services
Year
2011
Tongue
English
Weight
482 KB
Volume
18
Category
Article
ISSN
1005-9784

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## Abstract This paper considers the forecast accuracy of a wide range of volatility models, with particular emphasis on the use of power transformations. Where one‐period‐ahead forecasts are considered, the power autoregressive models are ranked first by a range of error metrics. Over longer forec