政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/99530
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 114401/145431 (79%)
造訪人次 : 53101561      線上人數 : 552
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧：
  • 您可在西文檢索詞彙前後加上"雙引號"，以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋，建議至進階搜尋限定作者欄位，可獲得較完整資料
    •  進階搜尋
    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/99530


    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/99530


    題名: 以機器學習方法估計電腦實驗之目標區域
    Estimation of Target Regions in Computer Experiments: A Machine Learning Approach
    作者: 林家立
    Lin, Chia Li
    貢獻者: 洪英超
    Hung, Ying Chao
    林家立
    Lin, Chia Li
    關鍵詞: 電腦實驗
    均勻設計
    反應曲面法
    分類模型
    computer experiment
    uniform design
    response surface methodology
    classification
    日期: 2016
    上傳時間: 2016-08-02 15:53:14 (UTC+8)
    摘要: 電腦實驗(computer experiment)是探索複雜系統輸出反應值和輸入參數之間關係的重要工具，其重要特性是每一次的實驗非常耗費時間及運算的成本。一般在電腦實驗中，研究者較常關心的多是反應曲面的配適和輸出反應值的最佳化等問題(如極大或極小值)。借由一真實平行分散處理系統的啟發，本文所關心的是如何找出系統反應值的局部目標區域。此目標區域有一個非常重要的特性，即區域內外的輸出值所呈現的反應曲面並不連續，因此一般傳統的反應曲面法(response surface methodology)無法適用。本文提出一個新的、可估計不同類型電腦實驗目標區域的有效方法，其中包含了逐步均勻設計和建立分類模型的概
    念，電腦模擬的結果也證明了所提方法準確又有效率。
    Computer experiment has been an important tool for exploring the relationships between the input factors and the output responses. It’s important feature is that conducting an experiment is usually time consuming and computationally expensive. In general, researchers are more interested in finding an adequate model for the response surface and the related output optimization problems over the entire input space. Motivated by a real-life parallel and distributed system, here we focus on finding a localized “target region” for the computer experiment. The experiment here has an important characteristic - the response surface is not continuous over the target region of interest. Thus, the traditional response surface methodology (RSM) cannot be directly applied. In this thesis, a novel and efficient methodology for estimating this type of target regions of computer experiment is proposed. The method incorporates the concept of sequential uniform design (UD) and the development of classification techniques based on support vector machines (SVM). Computer simulation shows that the proposed method can efficiently and precisely estimate the target region of
    computer experiment with different shapes.
    參考文獻: Box, G.E.P., Drapper, D.R., (1987), “Empirical Model Building and Response Surfaces,”
    John Wiley & Sons, New York.
    Chen, R.B., Hsu, Y.W., Hung, Y., Wang, W. (2012), “Central Composite Discrepany-
    Based Uniform Designs for Irregular Experimental Regions,” Computational Statistics & Data Analysis.
    Cheng, C.S., Li, K.C., (1995), “A study of the method of principal Hessian direction
    for analysis of data from design experiments,” Statistica Sinica 5, 617-639.
    Chuang, S.C., Hung, Y.C. (2010), “Uniform design over general input domains with
    applications to target region estimation in computer experiments,” Computational Statistics & Data Analysis, 54, 219-232.
    Fang, K.T., Lin, D.J., Winker, P., and Zhang, Y. (2000), “Uniform Design: Theory and
    Applications,“ Technometrics, 42, 237-248.
    Hickernell, F.J., (1999), “Goodness-of-fit statistics, discrepancies and robust designs,”
    Statistics & Probability Letters 44, 73-78.
    Huang, C.M., Lee, Y.J., Lin, D.K.J., Huang, S.Y., (2007), “Model selection for support vector machines via uniform design,” Computational Statistics & Data Analysis 52,
    335-346.
    Hung, Y.C., Chang, C.C., (2008), “Dynamic scheduling for switched processing systems with substantial service-mode switching times,” Queneing Systems: Theory
    and Applications 60, 87-109.
    Johnson, M.E., Moore, L.M., and Ylvisaker, D. (1990), “Minimax and Maximin
    Distance Designs,” Journal of Statistical Planning and Inference. 26. 131-148.
    Keerthi, S.S., Lin, C.J., (2003), “Asymptotic behaviors of support vector machines
    with Gaussian kernel,” Neural Computation 15, 1667-1689.
    McKay, M.D., Beckman, R.J., and Conover, W.J. (1979), “A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a
    Computer Code,” Technometrics, 21, 239-245.
    Owen, A.B. (1992), “Orthogonal Arrays for Computer Experiments, Integration and
    Visualization,” Statistica Sinica, 2, 439-452.
    Ranjan, P., Bingham, D., and Michailidis, G. (2008), “Sequential Experimental Design for Contour Estimation From Complex Computer Codes,” Technometrics, 50, 527-
    541.
    Sacks, J., Welch, W.J., Mitchell, T.J., Wynn, H.P., (1989). “Design and Analysis of
    Computer Experiments,” Statistical Science, 4, 409-423.
    Tang, B. (1993), “Orthogonal Array-Based Latin Hypercubes,” Journal of the American
    Statistical Association, 88, 1392-1397.
    Vapnik, V.N., (1998), “Statistical Learning Theory,” Wiley, New York.
    Wang, D., Zhang, X., Fan, M. and Ye, X., (2015), “An Efficient Classifier Based on Hierarchical Mixing Linear Support Vector Machines,” IJCAI, AAAI Press, 3897-
    3903.
    Wu, C.F.J., Hamada, M., (2000), “Experiments: Planning, Analysis, and Parameter
    Design,” Wiley, New York
    描述: 碩士
    國立政治大學
    統計學系
    103354001
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0103354001
    資料類型: thesis
    顯示於類別:[統計學系] 學位論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    400101.pdf1265KbAdobe PDF296檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋