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題名：以實驗設計方法對倒傳遞網路學習參數進行最佳化的研究：於藥物動力學的應用為例
書刊名：管理與系統
作者：葉若春／鄭春生／卜玉枝
作者(外文)：Yeh, Yu-chuen／Cheng, Chuen-sheng／Pu, Yu-chih
出版日期：1999
卷期：6:1
頁次：頁65-91
主題關鍵詞：倒傳遞網路；藥物動力學；部份因子實驗設計；網路學習參數；Backpropagation neural network；Population pharmacokinetics；Fractional factorial design；Design parameters
原始連結：連回原系統網址new window
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  • 被引用次數被引用次數:期刊(2) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:2
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  • 點閱點閱:28
　　　　　對於倒傳遞網在藥物學上的應用，至今仍缺乏系統性的研究方法，來探究其最適化網路參數的設計。針對此問題本文提出一個以解析度為IV之28-3部分因子實驗設計，對網路架構內的八個設計因子(A~H)進行研究。由常態機率分布圖的結果指出：主要因均不顯著，僅有兩個二因子交互作用(DH、AG+BD)具有顯著性。由於二因子交互作用交絡在一起，因此必須進行鏡射試驗使其相互分離。在結合主要試驗與鏡射試驗之後，將擁有足夠的情報以估算所有的主要因與二因子交互作用；此時方可建立合適的模式去設計確認試驗。在確認試驗的實測值與預估值極為相近，且滿足殘差的三大基本假設時，該實驗的適切性即可獲得驗證。因此本研究顯示：倒傳遞網路在人口藥物動力學上的應用，以部份因子實驗設計進行最佳化，確實為一可行且有效的分析工具。
　　　　　Currently there is lack of a systemic approach to select the optimal design parameters for pharmaceutical applications when the backpropagation neural networks are used in the field. In order to deal with this problem, a resolution IV 28-3 fractional factorial design is employed to investigate the effects of 8 design factors (A~H) on the neural network configuration. A result of the normal probability plot reveals that main effects are not significant, two largest effects are two-factor interactions (DH、Ag+BD). Due to confounding among the two-factor interactions, the principal fraction allows a sequential investigation to separate the two-factor interactions by foldovering the design. The combined design gives sufficient information to estimate all of the main effects and two-factor interactions, then we have developed the fitted model for designing the confirmation experiments. If the estimated values in the confirmation experiments are close to the expected intervals and the assumptions of the model are ascertained, then we can conclude that the combined design is fundamentally adequate. The result drawn from this research shows that the fractional factorial design provides an efficient means to optimize the design parameters of a backpropagation neural network applied in population pharmacokinetics.
期刊論文
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17.Jones, K. F.、Marrs, I.、Townend, Y. C.(1995)。Investigation and Improvement of a Process for Vacuum-formed Ceramic Fibre Composites, Using a Fractional in Experimental Design。Journal of Applied Statistics，22(4)，459-467。  new window
18.Kempka, A. A.(1994)。Activating Neural Networks。AI Expert，1994(Jun.)，33-37。  new window
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會議論文
1.Chiu, C. C.、Pignatiello, J. J.、Cook, D. F.(1994)。Response Surface Methodology for Optimal Neural Network Selection。Sixth International Conference on Tools with Artificial Intelligence。Los Angeles：IEEE。161-167。  new window
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學位論文
1.卓高平(1996)。類神經網路最佳學習參數值找尋之研究:以空調溫濕度異常診斷與處理為例(碩士論文)。元智工學院。  延伸查詢new window
圖書
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圖書論文
1.Fernández, B.(1994)。Performance Analysis of Artificial Neural Networks Methods。Artificial Neural Networks for Intelligent Manufacturing。London：Chapman & Hall。  new window
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