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The Optimal Weighted Combinational Forecasting with Constant Terms 被引量：1

The Optimal Weighted Combinational Forecasting with Constant Terms
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摘要 We propose a model based on the optimal weighted combinational forecasting with constant terms, give formulae of the weights and the average errors as well as a relation of the model and the corresponding model without constant terms, and compare these models. Finally an example was given, which showed that the fitting precision has been enhanced.
作者 ZHANG Jian-guo
机构地区 College of Mathematics and Information Science
出处 《Chinese Quarterly Journal of Mathematics》 CSCD 北大核心 2007年第1期109-113,共5页 数学季刊（英文版）
基金 Supported by the Natural Science Foundation of Henan Province(994053200)
关键词 combinational forecasting constant term combinational weight fitting deviation 常数项 组合预测 加权 优化
分类号 O212.1 [理学—概率论与数理统计]
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参考文献3

  • 1TANG Xiao-wo. The optimal combinational forecasting method and its application[J]. The Mathematical Statistics and Managements, 1992, (1): 31-35.
  • 2ZHANG You-lane et al. The optimal weighted combinational forecasting and its application[J]. The Quantity Economy and the Technical Economy Study, 1997,(10): 66-68.
  • 3XIE Bang-jie. Linear Algebra[M]. Beijing: The People Education Publishing House, 1978.

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  • 1Yang X S. Nature-inspired metaheuristic algorithms[M]. New York: Luniver Press, 2008.
  • 2Nezih A, Lewis A L. Service parts management: demand forecas- ting and inventory control[M]. London: Springer Press, 2011.
  • 3Yager R R. Induced aggregation operators[J]. Fuzzy Sets and Systems, 2003, 137(1): 59-63.
  • 4Xu Z S, Da Q L. The ordered weighted geometric averaging op- erators[J]. International Journal of Intelligent Systems, 2002, 17(6) : 709 - 716.
  • 5Snyder R D, Ralph D K, Anne B O, et al. Forecasting for in- ventory control with exponential smoothing [J].International Journal of Forecasting, 2002, 18(1) : 5 - 18.
  • 6Ji L G, Zhang S N, Zhou M. A new GM(1,1) model for predic- ting oscillation date sequence [ C ] // Prognostics & System Health Management Conference, 2011 : 257 - 259.
  • 7Suykens J A K, Van Gestel T, De Brabanter J, et al. Least squares support vector machines [M]. Singapore: World Scien- tific Publishing Co. Pte. Ltd. , 2002.
  • 8Olivier C, Vladimir V, Olivier B, et al. Choosing multiple pa- rameters for support vector machines[J]. Machine Learning, 2002, 46(7): 131-159.
  • 9Gavin C C, Nicola L C T. Improved sparse least-squares sup- port vector machines[J]. Neurocomputing, 2002, 48 (10) : 1025 - 1031.
  • 10Dai C H, Chen W R, Zhu Y F, et al. Seeker optimization algo- rithm for optimal reactive power dispatch[J]. IEEE Trans. on Power Systems, 2009, 24(3): 1218- 1231.

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二级引证文献7

Chinese Quarterly Journal of Mathematics
2007年 第1期

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