請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/41183
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 張斐章(Fi-John Chang) | |
dc.contributor.author | Wan-Jyun Li | en |
dc.contributor.author | 李婉君 | zh_TW |
dc.date.accessioned | 2021-06-14T17:22:19Z | - |
dc.date.available | 2008-08-05 | |
dc.date.copyright | 2008-08-05 | |
dc.date.issued | 2008 | |
dc.date.submitted | 2008-07-24 | |
dc.identifier.citation | Beard, D., 2006. Using VRML to share large volumes of complex 3D geoscientific information via the Web. Proceedings of the eleventh international conference on 3D web technology: 163-167.
Behr, J., Dahne, P. and Roth, M., 2004. Utilizing X3D for immersive environments. Proceedings of the ninth international conference on 3D Web technology: 71-78. Buttussi, F., Chittaro, L. and Nadalutti, D., 2006. H-animator: a visual tool for modeling, reuse and sharing of X3D humanoid animations. Proceedings of the eleventh international conference on 3D web technology: 109-117. Chang, F.J. and Chang, Y.T., 2006. Adaptive neuro-fuzzy inference system for prediction of water level in reservoir. Advances in Water Resources, 29(1): 1-10. Chang, L.C., 2008. Guiding rational reservoir flood operation using penalty-type genetic algorithm. Journal of Hydrology. Chang, L.C. and Chang, F.J., 2001. Intelligent control for modelling of real-time reservoir operation. HYDROLOGICAL PROCESSES, 15(9): 1621-1634. Chang, Y.T., Chang, L.C. and Chang, F.J., 2005. Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves. HYDROLOGICAL PROCESSES, 19(7): 1431-1444. Chaves, P. and Chang, F.J., 2008. Intelligent reservoir operation system based on evolving artificial neural networks. Advances in Water Resources. Cooper, D. and LaRocca, G., 2007. Knowledge-based Techniques for Developing Engineering Applications in the 21st Century. 7 th AIAA Aviation, Technology, Integration, and Operations Conference(ATIO) Proceedings. Coulibaly, P., Anctil, F. and Bobee, B., 2000. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach. Journal of Hydrology, 230(3-4): 244-257. Hecht-Nielsen, R., 1987. Counterpropagation networks. Applied Optics, 26(23): 4979-4984. Hetherington, R., Farrimond, B. and Presland, S., 2006. Information rich temporal virtual models using X3D. Computers & Graphics, 30(2): 287-298. Hopfield, J.J., 1982. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. Proceedings of the National Academy of Sciences of the United States of America, 79(8): 2554-2558. Huang, Z., Eliens, A. and Visser, C., 2002. STEP: A Scripting Language for Embodied Agents. Proceedings of the Workshop of Lifelike Animated Agents, Tokyo. Jain, S.K., Das, A. and Srivastava, D.K., 1999. Application of ANN for Reservoir Inflow Prediction and Operation. Journal of Water Resources Planning and Management, 125(5): 263-271. Kohonen, T., 1982. Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43(1): 59-69. Marovi, B. and Jovanovi, Z., 2006. Web-based grid-enabled interaction with 3D medical data. Future Generation Computer Systems, 22(4): 385-392. McCulloch, W.S. and Pitts, W., 1943. A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biology, 5(4): 115-133. Melzer, K., Lipinski, H.G. and Gronemeyer, D.H.W., 2004. X3D-technologies for medical image visualization. International Conference on Computer Graphics and Interactive Techniques. Nadalutti, D., Chittaro, L. and Buttussi, F., 2006. Rendering of X3D content on mobile devices with OpenGL ES. Proceedings of the eleventh international conference on 3D web technology: 19-26. Rumelhart, D.E. and McClelland, J.L., 1986. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations. Mit Press Computational Models Of Cognition And Perception Series: 547. Soares, L.P. and Zuffo, M.K., 2004. JINX: an X3D browser for VR immersive simulation based on clusters of commodity computers. Proceedings of the ninth international conference on 3D Web technology: 79-86. Sutherland, I.E., 1965. The Ultimate Display. Proceedings of the IFIP Congress, 2(506-508). Web3D, 1997. ISO/IEC 14772-1:1997 and ISO/IEC 14772-2:2004 — Virtual Reality Modeling Language (VRML) http://www.web3d.org. Web3D, 2004. IISO/IEC 19775:2004 — Extensible 3D (X3D). http://www.web3d.org/x3d/specifications/. Web3D, 2005a. ISO/IEC 19776-1:2005/Am1—X3D encodings: XML encoding: Amendment 1. http://www.web3d.org/x3d/specifications/ISO-IEC-19776-2-Amendment1-X3DEncodings-XML/. Web3D, 2005b. ISO/IEC 19776-2:2005/FDAm1—X3D encodings: Classic VRML encoding: Amendment 1. http://www.web3d.org/x3d/specifications/ISO-IEC-19776-2-Amendment1-X3DEncodings-ClassicVRML/. Web3D, 2005c. ISO/IEC 19776-3—X3D encodings: Binary encoding. http://www.web3d.org/x3d/specifications/ISO-IEC-19776-3-X3DEncodings-CompressedBinaryEncoding/. Web3D, 2005d. ISO/IEC 19777-1:2005—X3D language bindings:ECMAScript. http://www.web3d.org/x3d/specifications/ISO-IEC-19777-1-X3DLanguageBindings-ECMAScript/. Web3D, 2005e. ISO/IEC 19777-2:2005—X3D language bindings: Java. http://www.web3d.org/x3d/specifications/ISO-IEC-19777-2-X3DLanguageBindings-Java/. Web3D, 2007. ISO/IEC CD 19775-2.2:200x—X3D Scene application interface Edition 2. http://www.web3d.org/x3d/specifications/ISO-IEC-CD-19775-2.2-X3D-SceneAccessInterface/index.html. Web3D, 2008. ISO/IEC FDIS 19775-1.2:2008—X3D Architecture and base components Edition 2. http://www.web3d.org/x3d/specifications/ISO-IEC-FDIS-19775-1.2-X3D-AbstractSpecification/index.html. Yin, S. and Eliens, A., 2007. PANORAMA: A Rich VRML Application Platform For Online Gaming. WEB3D GAMES 2007. 王國威,2006,運用懲罰機制遺傳演算法於水庫洪颱操作之規則,淡江大學水資源及環境工程學系研究所碩士論文。 向子菁,1999,智慧型控制理論於水庫操作決策之研究,國立台灣大學農業工程研究所碩士論文。 邱昱禎,2003,模糊規劃理論與優選法於水庫操作之研究,國立臺灣大學生物環境系統工程學系暨研究所碩士論文。 張郁麟,2007,倒傳遞類神經網路應用於台灣北部水庫懸浮固體濃度即時分析與預測之研究. 國立臺灣大學生物環境系統工程學系暨研究所碩士論文。 張斐章、張雅婷、張麗秋,2004,結合人工智慧與專家知識之智慧型水庫操作系統. 農業工程學報, 50(4):14-27。 張斐章、張麗秋,2005,類神經網路. 東華書局。 張雅婷, 2006,調適性網路模糊推論系統於水庫操作之研究,國立臺灣大學生物環境系統工程學系暨研究所碩士論文。 陳莉,1995,以物件導向之遺傳演算法優選水庫運用規線之研究,國立臺灣大學農業工程學研究所博士論文。 葉怡成,2003,類神經網路模式應用與實作,儒林出版社。 蔡斐毓,2006,類神經網路於颱風降雨與流量預報之研究,國立台灣大學土木工程學研究所博士論文。 賴進松、張向寬、李豐佐,2004,員山子分洪工程對汐止五堵地區淹水之模擬分析與虛擬實境展示,台灣水利,第五十二卷(第二期):pp.58-68。 羅華強,2001,類神經網路-MATLAB 的應用,清蔚科技公司。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/41183 | - |
dc.description.abstract | 為使水庫之營運在防汛時期有精確的操作策略與視覺化之操作介面,本研究建立了一種模擬操作模式與兩種即時操作模式供水庫操作參考;模擬操作乃根據前人以遺傳演算法(Genetic Algorithms, GA)所得到之最佳操作歷程,設計ㄧ洩放流程,模擬水庫各個設施實際可行之操作方式,亦檢測了不同閘門開度條件下所得之結果;研究顯示,總洩放量與期末水位幾乎可達到GA所設之目標,模擬的成效相當良好。在即時操作部份,本研究提供了兩種模式,第一種操作僅以目標水位為導向,不考慮複雜的演算法;第二種操作則是以GA之結果,做為倒傳遞類神經網路之訓練標的,推估下一時刻目標水位。即時操作的結果顯示,以目標水位為標的的操作模式較為保守,能夠使水位快速的達到所期望之高程,但在洪峰消減率上則表現較不佳;而倒傳遞類神經網路操作之結果不論在洪峰消減率或是期末水位的表現上,皆較原操作佳,能有效改善原操作的不確定性及不平滑性。此外,為使研究成果能有效展示,本文應用新一代網路三維標準格式X3D(Extensible 3D, X3D)作為展示介面。X3D的格式不僅可在水文資訊系統上達到快速的資料傳遞整合工作,更可讓決策者以視覺化的方式看到資料的即時變化情形及相關水庫操作決策之影響,是結合水文系統分析及網路資訊設計的ㄧ大趨勢,可做為水文資訊平台之應用。 | zh_TW |
dc.description.abstract | In order to develop a more precise strategy and a visional interface for the management of reservoir during typhoon or heavy rainfall events, this study provides a simulated control model and two real-time control models for reservoir operation. The flood release process has been designed in simulation control model to simulate the feasible operations of every reservoir facility according to the best result of Genetic Algorithms(GA) obtained from a previous study. Besides, performances from different level of open-gap in the release gate are verified. The results indicate that the simulated outcomes are fairly good and both total amount of outflow and the water demand are similar as those searched by GA. This study provides two real-time control models; the first one is merely derived from target water levels, and no complex algorithms; the second real-time control model uses the results simulated by GA as training patterns for Back Propagation Network(BPN)to estimate water release at next hour. Results from first model show the water level can rapidly reach the designed target but performance on the reduction of flood peak rate is not good enough. Whereas, results gained from BPN model not only produce better reduction of flood peak rate but also reach the target at the end of the flood. Moreover, both uncertainty and smoothly existed in original reservoir operation can be effectively improved through BPN model. In addition, a new generation of three-dimensional standard format X3D(Extensible 3D, X3D)is applied herein to display the on-line operating results. X3D can efficiently achieve the goal of data communication and integration in hydroinformatic system. Furthermore, the variation of data structure and the impact of operational strategy can be easily received and understood by decision maker in visional way. It is a tendency to combine hydrological analysis and information design on the Web. | en |
dc.description.provenance | Made available in DSpace on 2021-06-14T17:22:19Z (GMT). No. of bitstreams: 1 ntu-97-R95622029-1.pdf: 22638859 bytes, checksum: ab4ad1a7e680bbc61670b707b0ef9ea7 (MD5) Previous issue date: 2008 | en |
dc.description.tableofcontents | 摘 要 I
Abstract II 目 錄 IV 圖目錄 VII 表目錄 X 壹、緒論 1 1-1 研究動機 1 1-2 研究目的與方法 1 貳、文獻回顧 4 2-1類神經網路 4 2-2水庫操作 5 2-3類神經網路於水庫操作 6 2-4 X3D 7 2-4.1VRML/ X3D發展歷程 7 2-4.2 X3D虛擬實境應用 9 參、理論概述 11 3-1類神經網路 11 3-2倒傳遞類神經網路 13 3-2.1倒傳遞類神經網路之基本架構與特性 13 3-2.2誤差倒傳遞演算法 14 3-3 X3D基本架構及規範 19 肆、研究案例 21 4-1石門水庫簡介及概況 21 4-2各放流設施說明 22 4-2.1溢洪道閘門洩放量 25 4-2.2排洪隧道閘門洩放量 33 4-2.3其餘放流機制 37 4-2.4永久河道放水口洩放量 37 4-3洩放流程 38 4-3.1總洩放量決定 39 4-3.2各設施洩放第一步驟 41 4-3.3各設施洩放第二步驟 42 4-3.4各設施洩放第三步驟 50 4-4水文資料選取 51 伍、模擬結果 52 5-1 操作策略1---GA模擬操作 53 5-1.1模擬結果 53 5-1.2 開度範圍比較 55 5-2操作策略2---目標水位即時操作 57 5-2.1操作流程 57 5-2.3操作結果 59 5-3操作策略3---BPN操作 61 5-3.1 BPN網路架構輸入因子 62 5-3.2 BPN網路架構資料 64 5-3.3 BPN推估結果 66 5-4 X3D虛擬實境介面設計 72 5-4.1製作流程 72 5-4.2 GA模擬結果 76 5-4.3 BPN即時操作結果 80 六、結論與建議 85 6-1結論 85 6-2建議 86 參考文獻 88 附錄 A---GA模擬操作 93 附錄 B---目標水位即時操作 102 附錄C---BPN即時操作 111 | |
dc.language.iso | zh-TW | |
dc.title | 以類神經網路為基礎的X3D虛擬實境模擬水庫即時操作----以石門水庫為例 | zh_TW |
dc.title | Simulation of Real-Time Operation by ANN-Based X3D Virtual Reality for the Shihmen Reservoir | en |
dc.type | Thesis | |
dc.date.schoolyear | 96-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 賴進松(Jihn-Sung Lai),張麗秋(Li-Chiu Chang),陳宏?(Hung-Kwai Chen) | |
dc.subject.keyword | 類神經網路,水庫防洪即時操作,X3D,虛擬實境, | zh_TW |
dc.subject.keyword | ANNs,Reservoir real-time flood Operation,X3D,Virtual Reality, | en |
dc.relation.page | 119 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2008-07-26 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-97-1.pdf 目前未授權公開取用 | 22.11 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。