臺灣博碩士論文加值系統

網路使用的普及率是衡量一國科技競爭力的重要指標之一。因此網路用戶數的精確預測成為政府在規劃經濟建設與跨國企業進行商務投資時重要的參考資訊。在網際網路用戶數成長逐漸趨於飽和特性下，本論文結合灰色Verhulst模型(GVM)及累加調和平均法，提出改良模型(H-GVM)以進一步提高網際網路用戶數之預測效率。研究結果發現，當網路擴散逐漸趨於成長飽和時，GVM、 H-GVM兩者均較傳統最小平方法在樣本外預測上更具精確度。此外，本論文所提出的H-GVM在預測網際網路經常用戶數及商用網路用戶數其平均絕對預測誤差(MAPE)分別為0.08％及2.33％，均較GVM的MAPE小，顯示本研究所提出的預測模式可進一步提高GVM的預測精確度。本研究結果亦可供政府進行短期公共政策規劃及企業商業投資評估與短期預測之參考。

An accurate prediction of the ever-increasing volume of Internet participants is of great value to enterprises in realizing the potential market of business conducted via an electronic medium. In addition, it can aid governments in enacting appropriate public plans. This research applied an integrated prediction approach by combining the Grey Verhulst Model (GVM) with a four-point rolling technique, and also utilized a harmonic-mean-smoothing technique to forecast the number of Internet participants in a gradually saturated market. The mean absolute percentage error criterion was used to compare the performance of our proposed model against three other models: the Ordinary Least Squares Model, the traditional Grey Prediction Model GM(1,1), and the GVM. Empirical results indicate that the GVM is better suited to short-term prediction than the traditional Grey Prediction Model GM(1,1) for gradually saturated systems. Meanwhile, our approach not only helps improve the short-term prediction accuracy of the GVM, but it also outperformed the other two models.

第1章 緒論.................... 1
第1.1節 研究背景.......... 1
第1.2節 研究動機.......... 3
第1.3節 研究目的.......... 4
第1.4節 研究流程.......... 5

第2章 文獻探討.......... 6
第2.1節 灰色理論.......... 6
第2.2節 灰色預測.......... 8
第2.3節 修正灰色預測模式.. 10
第2.4節 網路發展與擴散.... 12

第3章 研究方法................. 15
第3.1節 最小平方法........ 15
第3.2節 灰色模型GM(1,1)... 15
第3.3節 灰色Verhulst模型.. 17
第3.4節 灰色Verhulst修正模型..21
第3.5節 預測誤差衡量...... 26

第4章 研究分析與討論............ 28
第4.1節 資料來源......... 28
第4.2節 結果與討論....... 29
第5章 研究結論與建議............ 33
第5.1節 研究結論......... 33
第5.2節 研究限制與建議..... 34
參考文獻 ..........................35
一、中文部份............... 35
二、西文部份............... 36

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