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系統識別號 U0026-0812200914120445
論文名稱(中文) 應用類神經網路與關聯規則於供應商選擇之研究
論文名稱(英文) A Study of Neural Network and Association Rule on Supplier Selection
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系專班
系所名稱(英) Department of Industrial and Information Management (on the job class)
學年度 96
學期 2
出版年 97
研究生(中文) 張永章
研究生(英文) Yung-chang Chang
學號 r3795124
學位類別 碩士
語文別 中文
論文頁數 60頁
口試委員 口試委員-翁慈宗
口試委員-王維聰
指導教授-王惠嘉
中文關鍵字 關聯規則  類神經網路  供應商選擇 
英文關鍵字 Association Rule  Neural Network  Supplier Selection 
學科別分類
中文摘要 在全球化經濟及供應鏈管理的趨勢下,企業需透過與外部資源的整合以產生競爭力,供應商的選擇對於企業來說已經成為一個控制產品成功與否的關鍵因素,如何幫助企業選擇正確的供應商是一個急迫且待解決的問題。另一方面,企業與供應商已從傳統的敵對關係逐漸轉向為相互依存的合作關係,企業的管理範圍已從內部運作擴及外部供應商,因此,如何協助與管理供應商,讓他們成為供應鏈的助力,也是企業必須面臨的問題。
本研究以某企業供應商為研究對象,以類神經網路(Neural Network)及關聯規則(Association Rule)建立供應商評選模式。第一階段應用類神經網路(Neural Network)中的倒傳遞網路(Back Propagation Network, BPN)建立供應商評等之分類,以區分供應商之績效類別,同時進行模式訓練及驗證,以確保模式之穩定性;第二階段利用類神經網路分類後之供應商資料,以關聯規則(Association Rule)找出不同類型供應商之特徵及規則;最後利用類神經網路分類及關聯規則資料建立供應商評選模式,提供企業選擇供應商決策之參考,提升供應鏈管理的績效。
英文摘要 Under globalization environment, enterprises need to integrate external resources to increase competitiveness. How to help companies in selecting proper suppliers has become an important issue. In this study, we use Neural Network and Association Rules to establish a supplier selection model. The first phase adopts Back Propagation Network(BPN) to establish supplier rating classification. It aims to distinguish between providers of performance categories, while a model training and certification to ensure that Model of stability. The second phase trains association rule to identify different types of characteristics of each classification. A selection model has been proposed to combine the rule information and neural network classification to establish supplier selection model. The suggested supplier list provide a reference for decision-making in supplier selection which should be able to enhance the performance of supply chain management.
論文目次 目錄 V
表目錄 VII
圖目錄 VIII
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究範圍與限制 3
1.4 研究方法與架構 3
第二章 文獻探討 5
2.1 供應商選擇 5
2.1.1 供應商選擇準則 5
2.1.2供應商選擇方法 8
2.2 資料探勘 11
2.3 類神經網路 14
2.4 倒傳遞網路 16
2.5 關聯規則 20
2.6 小結 21
第三章 研究方法 23
3.1 研究架構 23
3.2 以類神經倒傳遞網路進行供應商績效分類 26
3.2.1 輸入層設定 27
3.2.2 隱藏層設定 28
3.2.3 轉換函數設定 29
3.2.4 評估標準 29
3.2.5 收斂條件 29
3.2.6 學習速率與慣性項 30
3.3 關聯規則分析 31
3.4 建立供應商評選模式 34
第四章 實作驗證 36
4.1 資料來源 36
4.2類神經網路供應商績效分類 39
4.2.1 資料前置處理 39
4.2.2 類神經網路參數設定 40
4.2.3 類神經網路模式驗證及結果分析 42
4.3關聯規則分析 47
4.3.1 資料前置處理 48
4.3.2 關聯規則參數設定 49
4.3.3 關聯規則驗證與結果分析 50
4.4 建立供應商評選模式 53
第五章 結論與建議 56
5.1 結論 56
5.2 未來研究建議 57
參考文獻 58
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