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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭克聲(Ke-Sheng Cheng) | |
dc.contributor.author | Hsien-Wei Chen | en |
dc.contributor.author | 陳弦韋 | zh_TW |
dc.date.accessioned | 2021-06-16T07:02:56Z | - |
dc.date.available | 2014-07-15 | |
dc.date.copyright | 2014-07-15 | |
dc.date.issued | 2014 | |
dc.date.submitted | 2014-07-14 | |
dc.identifier.citation | 1. Ahuja, R.K.; Magnanti, T.L.; Orlin, J.B. Network Flows: Theory, Algorithms, and Applications. Prentice Hall, NJ, USA, 1993.
2. Bazaraa, M.S.; Jarvis, J.J.; Sherali, H.D. Linear Programming and Network Flows. Wiley, USA, 2009. 3. Brendecke, C.M.; DeOreo, W.B.; Payton, E.A.; Rozaklis, L.T. Network Models of Water Rights and System Operations. Journal of Water Resources Planning and Management 1989, 115, 684-696. 4. Cheng, K.-S.; Hou, J.-C.; Liou, J.-J.; Wu, Y.-C.; Chiang, J.-L. Stochastic simulation of bivariate gamma distribution: a frequency-factor based approach. Stochastic Environment Research and Risk Assessment 2011, 25, 107-122. 5. Chow, V.T. A general formula for hydrologic frequency analysis. Trans Am Geophys Union 1951, 32, 231-237. 6. Chow, V.T.; Maidment, D.R.; Mays, L.W. Applied hydrology, McGraw-Hill, New York, USA, 1988. 7. Hsu, N.-S.; Cheng, K.-W. Network Flow Optimization Model for Basin-Scale Water Supply Planning. Journal of Water Resources Planning and Management 2002, 128, 102-112. 8. Kite, G.W. Frequency and risk analysis in hydrology. Water Resources Publications, CO, USA, 1988. 9. Loucks, D.P. Some Comments on Linear Decision Rules and Chance Constraints. Water Resources Research 1970, 6, 668-671. 10. Loucks, D.P.; Dorfman, P.J. An Evaluation of Some Linear Decision Rules in Chance-Constrained Models for Reservoir Planning and Operation. Water Resources Research 1975, 11, 777-782. 11. Loucks, D.P.; Stedinger, J.R.; Haith, D.A. Water Resource Systems Planning and Analysis. Prentice Hall, NJ, USA, 1981. 12. McBride, R.D. Solving embedded generalized network problems. European Journal of Operational Research 1985, 21, 82-92. 13. ReVelle, C.; Joeres E.; Kirby, W. The Linear Decision Rule in Reservoir Management and Design, 1, Development of the Stochastic Model. Water Resources Research 1969, 5, 767-777. 14. ReVelle, C.; Kirby, W. Linear Decision Rule in Reservoir Management and Design, 2, Performance Optimization. Water Resources Research 1970, 6, 1033-1044. 15. Sun, Y.-H.; Yeh, W.-G.; Hsu, N.-S. Generalized Network Algorithm for Water-Supply-System Optimization. Journal of Water Resources Planning and Management 1995, 121, 392-398. 16. Wilson, E.B.; Hilferty, M.M. The Distribution of Chi-square. Proceedings of the National Academy of Sciences USA 1931, 17, 684-688. 17. Yeh, W.-G. Reservoir Management and Operations Models: A State-of-the-Art Review. Water Resources Research 1985, 21, 1797-1818. 18. 經濟部水利署(2010)「九十九年蓄水設施營運水量統計」。 19. 劉佳明(1988)「水庫標的線性規劃問題之網路切割解法簡介」,台灣水利,36(2)。 20. 劉佳明(1997)「水庫標的規劃模式與其網路演算法」,86年農業工程研討會論文集。 21. 劉佳明(1999)「線性放水規則水庫線性規劃模式網路特性」,88年農業工程研討會論文集。 22. 劉佳明(2002)「水庫規劃問題的位勢與流量網絡模式」,農業工程學報,48(4)。 23. 劉佳明(2004)「水庫標的線性規劃模式及其對偶模式-網絡解釋」,農業工程學報,50(1)。 24. 劉佳明(2006)「位勢網絡法分析水庫容量」,農業工程學報,52(4)。 25. 劉佳明(2008)「線性供水規則下水庫容量規劃模式-位勢網絡解釋與算法」,農業工程學報,54(4)。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57775 | - |
dc.description.abstract | 本研究提出了一個不同以往的水庫操作規則。在本研究中,操作規則是藉由建立未來水位的序率過程的模型而得,而非傳統的藉由建立最佳化模型而得。這包含了(1)雙變數伽碼隨機變數的統計性質的推導。特別是,本研究給出了一個重要的的規則,即由一對雙變數伽碼隨機變數的相加或相減所產生的新隨機變數依然近似於伽碼隨機變數。(2)將雙變數伽碼隨機變數推廣至伽碼時間序列,進而建立入流時間序列的模型。並建立伽碼時間序列建模及模擬的程序。(3)藉由入流及出流的水平衡和雙變數伽碼隨機變數的統計性質,建立未來水位的伽碼時間序列模型。(4)藉由模擬未來水位的伽碼時間序列的模型,評估風險水位的發生機率,進而給定最終的操作規則。
一但建立最終的操作規則後,規則本身是定義明確且容易執行。機率的機制已被引入,因此它可結合長期、短期及多目標操作於一個最佳化中。分析所需的唯一材料是入流資料,因此,它亦可被應用於在興建新水庫前,估計滿足需求所需的水庫容量大小。 | zh_TW |
dc.description.abstract | A totally different reservoir operation rule is proposed here. In this study, the operation rule is obtained by modeling the stochastic process of future water levels instead of the traditional optimization modeling approaches. This involves (1) the derivation of statistical properties of bivariate gamma random variables, especially, this study gives an important rule that the random variable obtained by adding or subtracting a pair of gamma random variables is still approximately a gamma random variable, (2) extending bivariate gamma random variables to gamma time series to model the inflow time series, and establishing the modeling and simulation procedure of gamma time series, (3) establishing the gamma time series model for future reservoir water levels via the water balance between inflows and outflows and the statistical properties of bivariate gamma random variables, (4) the final operation rule is simply given by evaluating the probabilities of the occurrence of risk water levels via simulating realizations from the gamma time series model of the future water level.
Once the final operation rule is established, the rule itself is well-defined and easy-to-implement. It is able to combine long term, short term, and multi-goals operations to one optimization because the probability mechanism has been given. The only needed material for the analysis is the inflow data, thus, it can also be applied to estimate the required storage size to fulfill needs before building a new reservoir. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T07:02:56Z (GMT). No. of bitstreams: 1 ntu-103-R99622006-1.pdf: 8071941 bytes, checksum: dfc950186557eff8f4f939e3190275a0 (MD5) Previous issue date: 2014 | en |
dc.description.tableofcontents | 口試委員會審定書……………………………………………………………….........…i
Abstract…………………………………………………………......……………………ii 摘要………………………………………………………………….......………………iv Introduction…………………………………………………….......……………………1 Bivariate Gamma Random Variables……………………………………………....…6 Gamma Time Series………………………………………………………………..…19 Reservoir Water Level…………………………………………………………...……22 Reservoir Operation…………………………………………………………...………27 Shihmen Reservoir…………………………………………………………….....……29 Conclusions…………………………………………………………….........…………45 References……………………………………………………………......……………47 Appendices………………………………………………………………......…………50 | |
dc.language.iso | en | |
dc.title | 水庫操作的不確定性分析:水庫水位的序率過程模型 | zh_TW |
dc.title | Uncertainty Analysis of Reservoir Operation: The Stochastic Process Model of Reservoir Water Level | en |
dc.type | Thesis | |
dc.date.schoolyear | 102-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇明道(Ming-Daw Su),黃文政(Wen-Cheng Huang) | |
dc.subject.keyword | 雙變數伽碼分佈,分佈轉換,伽碼時間數列,序率過程,序率模擬,頻率因子, | zh_TW |
dc.subject.keyword | Bivariate gamma distribution,Distribution transformation,Gamma time series,Stochastic process,Stochastic simulation,Frequency factor, | en |
dc.relation.page | 56 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2014-07-14 | |
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 |
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