基於類神經網路與交叉驗證法之田口方法(Taguchi method based on neural networks and cross validation methodology)

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Title:	基於類神經網路與交叉驗證法之田口方法(Taguchi method based on neural networks and cross validation methodology)
Authors:	葉怡成 Yeh, I-Cheng
Contributors:	資訊管理學系 Information Management
Keywords:	田口方法;類神經網路;交叉驗證法;敏感性分析 Taguchi;neural;analysis
Date:	2009
Issue Date:	2014-06-27 01:42:44 (UTC+8)
Abstract:	本文為了克服傳統的田口方法的缺點，提出基於類神經網路與交叉驗證法的田口方法，其要點有：(1) 採用交叉驗證法以克服類神經網路必須區隔實驗數據集為訓練集、測試集，導致訓練集數據不足的缺點。(2) 提出敏感性分析與帶狀主效果圖以改善類神經網路黑箱模型的缺點。(3) 採用非線性規劃以設計最佳品質因子的組合。為了證明本法可行，本研究以二個已發表的田口方法的實例進行實證。研究結果顯示：(1) 傳統的田口方法的未區隔資料集為測試集、訓練集之作法，其誤差被嚴重低估。(2) 在同樣使用可正確評估模型誤差的交叉驗證法下，本 To overcome the shortcomings of traditional Taguchi method, this study proposed a Taguchi method based on neural networks and cross validation methodology. Its main ideas included that (1) it used cross-validation methodology to overcome the shortcoming t
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