請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66045完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王偉仲 | |
| dc.contributor.author | Chung-Wei Chen | en |
| dc.contributor.author | 陳中偉 | zh_TW |
| dc.date.accessioned | 2021-06-17T00:20:02Z | - |
| dc.date.available | 2017-06-29 | |
| dc.date.copyright | 2012-06-29 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-06-25 | |
| dc.identifier.citation | [1] Atkinson, A. C. and Donev, A. N. (1992) Optimum Experimental De- signs, Oxford University Press, Oxford.
[2] Cook, R. D. and Nachtsheim, C. J. (1980) “A Comparison of algorithms for constructing exact D-optimal designs”. Techonmetrics, volume 22, pages 315-324. [3] de Aguiar, P. F., Bourguignon, B., Khots, M. S., Massart, D. L. and Phan-Than-Luu, R. (1995) “D-optimal Designs”. Chemometrics and In- telligent Laboratory Systems 30(2), pages 199210. [4] Fedorov, V. V. (1972) Theory of Optimal Experiments. (New York, Aca- demic Press) [5] Imhof, L. (1997) “Optimum Exact Designs for Polynomial Regression”. Ph.D Thesis, Aachen. [6] Kennedy, J. and Eberhart, R. C. (1995) “Particle Swarm Optimization”. In Proceedings of IEEE International Conference on Neural Networks, volume 4, pages 1942–1948. [7] Kiefer, J. (1959). “Optimum Experimental Designs”. Journal of the Royal Statistical Society, Series B 21, pages 272-319. [8] Mitchell, T. J. (1974) “An Algorithm for the Construction of D-optimal experimental designs” Techonmetrics, volume 16, pages 203-210. [9] Montepiedra, G., Myers, D. and Yeh, A. B. (1998) “Application of Genetic Algorithms to the Construction of Exact D-optimal Designs”. Journal of Applied Statistics, volume 25, No.6, pages 817-326. 33 [10] Rodriguez, M., Jones, B., Borror C.M. and Montgomery, D.C. (2010) “Generating and Assessing Exact G-optimal Designs” it Journal of Qual- ity Technology, volume 42, No.1, pages 3-20 [11] Yang, X. S. (2010) Engineering Optimization: An Introduction with Metaheuristic Applications. Wiley. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66045 | - |
| dc.description.abstract | 此篇論文主要探討在不同的準則下, 如何將粒子群演算法應用於尋找正合最適 實驗設計之中。 最適實驗設計的概念自從被提出後, 便普遍為科學以及工業領域所 採納且廣泛的應用, 而粒子群演算法為一新穎的最佳化方法, 可有效的解決複雜的 最佳化問題。 為尋找正合D-最適實驗設計, 我們提出了許多不同粒子群演算法的 變形, 相較於現今較為廣泛使用的演算法 MFE, 其中所提出的 PSO-mtb 也能在 短時間內提供類似的數值結果, 然而不論是 PSO 或 MFE, 在面臨多個變數的多 項式模型時, 都無法提供快速且良好的數值結果, 因此我們結合了這兩個演算法的 優點, 因而提出 MFE-PSO Hybrid 演算法, 在我們所有的測試中,MFE-PSO Hy- brid 演算法可以在短時間內提供相當優秀的數值結果, 在其他的準則中, 面對單變 數的多項式模型, 我們提出的方法也都能有良好的模擬結果, 然而, 在面對多變數 的多項式模型時, 能沒有有效的方法尋找正合G-最適實驗設計。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-17T00:20:02Z (GMT). No. of bitstreams: 1 ntu-101-R98221030-1.pdf: 1276134 bytes, checksum: 984b5a0777fc4ec1d727dd39ea4e380f (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | Abstract (in Chinese) i
Abstract (in English) ii Contents iii Figure List v Table List vi 1 Introduction 1 1.1 TheExactOptimalDesignProblem............... 2 1.2 ParticleSwarmOptimization .................. 3 2 Variants of PSO to the Exact D-optimal Design Problem 6 2.1 Algorithms for Construction of D-optimal Designs . . . . . . . 6 2.1.1 ModifiedFedorovMethod(MFE) . . . . . . . . . . . . 6 2.1.2 GeneticAlgorithm(GA)................. 8 2.2 PSO-mtb ............................. 10 2.3 NumericalResultsofPSO-mtb ................. 14 2.3.1 Single Factor 3rd Order Polynomial Model with 5 De- signPoints......................... 14 2.3.2 Single Factor 6th Order Polynomial Model with 50 De- signPoints......................... 15 2.4 MFE-PSOhybrid......................... 17 2.5 NumericalResultofMFE-PSO-hybrid . . . . . . . . . . . . . 20 2.5.1 3 Factors 3rd Order Polynomial Model with 25 Design Points ........................... 20 2.5.2 4 factors 3rd Order Polynomial Model with 40 Design Points ........................... 22 3 Variants of PSO to The Exact Design Problem under Other Criteria 25 3.1 ComparisonwithTheoreticalSolutions . . . . . . . . . . . . . 25 3.2 G-optimality............................ 29 4 Conclusion 31 | |
| dc.language.iso | en | |
| dc.subject | 粒子群演算法 | zh_TW |
| dc.subject | 最佳化設計準則 | zh_TW |
| dc.subject | 正合最適實驗設計 | zh_TW |
| dc.subject | 基因演算法 | zh_TW |
| dc.subject | 多項式模型 | zh_TW |
| dc.subject | polynomial model | en |
| dc.subject | optimality | en |
| dc.subject | exact optimal design | en |
| dc.subject | genetic algorithm | en |
| dc.subject | particle swarm optimization | en |
| dc.title | 用於正合最適實驗設計之新型態粒子群演算法 | zh_TW |
| dc.title | Variant Particle Swarm Optimizations for Exact
Optimal Design | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡碧紋,陳瑞彬 | |
| dc.subject.keyword | 最佳化設計準則,正合最適實驗設計,基因演算法,粒子群演算法,多項式模型, | zh_TW |
| dc.subject.keyword | optimality,exact optimal design,genetic algorithm,particle swarm optimization,polynomial model, | en |
| dc.relation.page | 34 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-06-25 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 數學研究所 | zh_TW |
| 顯示於系所單位： | 數學系 | |
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