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改進的新GM(1,1)模型及其建模精度研究

Research on a Novelly Improved Model of GM (1, 1) and Its Modeling Precision

摘要


根據灰色GM(1,1)的建模機理,分析了原灰色GM(1,1)建模參數固有的缺陷,在定理2中證明瞭GM(1,1)新的優化建模初始值,以此構建了新優化的GM(1,1)模型,並與原GM(1,1)及其優化模型進行了建模精度的比較。研究結果表明:新的優化GM(1,1)既適合低增長指數序列建模,也適合高增長指數序列建模,尤其當發展係數大於2時,新的GM(1,1)模型依然能保持非常高的建模精度。

並列摘要


According to the modeling mechanism of GM (1, 1) model, based on the analysis of the disadvantages of the original grey model GM (1, 1) modeling parameter. The Novelly optimized initial value of GM (1, 1) was proved in theorem 2, and the novel GM (1, 1) was constructed and compared with the original GM (1, 1) and its optimized models in modeling precision. The research findings indicate: the novelly optimized GM (1, 1) is not only suitable for the modeling for the low growth index sequence but also suitable for the modeling for the high growth index sequence. When the development coefficient is bigger than 2, the modeling precision (simulation precision and forecast precision) of the novel GM (1, 1) model is still very high.

參考文獻


鄧聚龍(1987)。累加生成灰指數律。華中工學院學報。15(2),7-12。
劉斌、趙亮、翟振傑(2003)。優化的GM(1,1)模型及其適用範圍。南京航空航太大學學報。4,451-454。
沈繼紅、趙希人(2001)。利用最小二乘估計改進GM(2,1)模型。哈爾濱工程大學學報。22(4),64-66。
譚冠軍(2000)。GM(1,1)模型的背景值構造方法和應用。系統工程理論與實踐。20(4),99-103。
羅黨、劉思峰、黨耀國(2003)。灰色模型GM(1,1)優化。中國工程科學。8,50-53。

被引用紀錄


黃桂芳(2015)。運用 Savitzky-Golay 濾波法改良灰色模型預測精度〔碩士論文,義守大學〕。華藝線上圖書館。https://doi.org/10.6343/ISU.2015.00055

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