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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 余化龍(Hwa-Lung Yu) | |
| dc.contributor.author | Ting-Hsin Chang | en |
| dc.contributor.author | 張丁心 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:28:28Z | - |
| dc.date.available | 2022-08-24 | |
| dc.date.copyright | 2017-08-24 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-08-18 | |
| dc.identifier.citation | J.Adamowski and Hiu Fung Chan. A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1–4):28 – 40, 2011. ISSN 0022-1694.
David P. Ahlfeld, John M. Mulvey, George F. Pinder, and Eric F. Wood. Contaminated groundwater remediation design using simulation, optimization, and sensitivity theory: 1. model development. Water Resources Research, 24(3):431–441, Mar 1988. ISSN 0043-1397. V. Batu. Aquifer Hydrqulics: A comprehensive Guide to Hydrogeologic Data Analysis, page 727p. John Wiley and Sons, 1998. Gedeon Dagan. An overview of stochastic modeling of groundwater flow and transport: From theory to applications. Eos, Transactions American Geophysical Union, 83(53): 621–625, 2002. ISSN 2324-9250. I. Daubechies. The wavelet transform, time-frequency localization and signal analysis.IEEE Transactions on Information Theory, 36(5):961–1005, Sep 1990. Clara Deser. On the teleconnectivity of the “arctic oscillation”. Geophysical Research Letters, 27(6):779–782, 2000. ISSN 1944-8007. Michael D. Dettinger and John L. Wilson. First order analysis of uncertainty in numeri- cal models of groundwater flow part: 1. mathematical development. Water Resources Research, 17(1):149–161, 1981. ISSN 1944-7973. P.A. Domenico and F.W. Schwartz. Physical and Chemical Hydrogeology, page 824p. John Wiley and Sons Sons, 1990. Margaret J. Eppstein and David E. Dougherty. Simultaneous estimation of transmissivity values and zonation. Water Resources Research, 32(11):3321–3336, 1996. ISSN 1944- 7973. Geir Evensen. Sequential data assimilation with a nonlinear quasi-geostrophic model us- ing monte carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99(C5):10143–10162, 1994. ISSN 2156-2202. Karl Pearson F.R.S. Liii. on lines and planes of closest fit to systems of points in space.Philosophical Magazine Series 6, 2(11):559–572, 1901. G. Golub and W. Kamhan. Calculating the singular values and pseudo-inverse of a ma- trix. Journal of the Society for Industrial and Applied Mathematics Series B Numerical Analysis, 2(2):pp.205–224, 1965. J. Jaime Go´mez-Herna´ndez and Andre´ G. Journel. Joint Sequential Simulation of Multi- Gaussian Fields, pages 85–94. Springer Netherlands, Dordrecht, 1993. P. Goupillaud, A. Grossmann, and J. Morlet. Cycle octave and related transforms in seismic signal analysis. Geoexploration, 23:85–102, 1984. Wendy D. Graham and Claude D. Tankersley. Forecasting piezometric head levels in the floridan aquifer: A kalman filtering approach. Water Resources Research, 29(11): 3791–3800, 1993. ISSN 1944-7973. A. Grossmann and J. Morlet. Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM Journal on Mathematical Analysis, 15(4):723–736, 1984. THOMAS L. GUNCKEL. Orbit determination using kalman’s method. Navigation, 10 (3):273–291, 1 1963. ISSN 2161-4296. Mohamed M. Hantush and Miguel A. Marin˜o. Two-dimensional stochastic analysis and optimal estimation in aquifers: Random recharge. Water Resources Research, 30(2): 559–569, 1994. ISSN 1944-7973. A. W. Harbaugh. Modflow-2005, the u.s. geologicla survey modular ground-water model- the groundwater flow process:u.s. geolofical survey techniques and methods 6-a16. Technical report, U.S. Department of the Interior, U.S. Geological Survey Reston, 2005. J. L. Harper, J. T. Williams, and G. R. Sagar. The behaviour of seeds in soil: I. the heterogeneity of soil surfaces and its role in determining the establishment of plants from seed. Journal of Ecology, 53(2):273–286, 1965. ISSN 00220477, 13652745. H. J. Hendricks Franssen and W. Kinzelbach. Real-time groundwater flow modeling with the ensemble kalman filter: Joint estimation of states and parameters and the filter inbreeding problem. Water Resources Research, 44(9):n/a–n/a, 2008. ISSN 1944-7973. W09408. Bill X. Hu, YanZhao Cao, WeiDong Zhao, and Feng Bao. Identification of hydraulic conductivity distributions in density dependent flow fields of submarine groundwater discharge modeling using adjoint-state sensitivities. Science China Earth Sciences, 59 (4):770–779, 2016. ISSN 1869-1897. P. Jacquard and C. Jain. Permeability distribution from field pressure data. Society of Petroleum Engineers, 5:281–294, 1965. A. I. Johnson. Specific yield: compilation of specific yields for various materials. Tech- nical report, U. S. Government Printing Office, Washington, D.C., 1967. R. E. Kalman. A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1):35–45, 1960. R. E. Kalman and R. S. Bucy. New results in linear filtering and prediction theory. Trans. ASME Ser. D. J. Basic Engrg., 83(1):95–108, 1961. E. J. Krakiwsky, C. B. Harris, and R. V. C. Wong. A kalman filter for integrating dead reckoning, map matching and gps positioning. In Position Location and Navigation Symposium, 1988. Record. Navigation into the 21st Century. IEEE PLANS ’88., IEEE, pages 39–46, 1988. Praveen Kumar and Efi Foufoula-Georgiou. Wavelet analysis for geophysical applica- tions. Reviews of Geophysics, 35(4):385–412, 1997. ISSN 1944-9208. K-M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. Bulletin of the American Meteorological Society, 76(12):2391–2402, 1995. E. N Lorenz. Empirical orthogonal functions of statistical weather prediction. Cam- bridge, Mass. : M.I.T., Dept. of Meterology, 1956, 1956. Peter S. Maybeck. Stochastic models, estimation, and control, volume 1. Academic Press, Inc, 1979. D. McLaughlin. An integrated approach to hydrologic data assimilation: interpolation, smoothing, and filtering. Advances in Water Resources, 25(8–12):1275 – 1286, 2002. ISSN 0309-1708. J. D. McLean, S. F. Schmidt, and L. A. McGee. Optimal filtering and linear prediction applied to a midcourse navigation system for the circumlunar mission. National Aero- nautics and Space Administration, 1962. James McPhee and William W.-G. Yeh. Groundwater management using model reduc- tion via empirical orthogonal functions. Journal of Water Resources Planning and Management, 134(2):161–170, 2008. Anna M. Michalak and Peter K. Kitanidis. Estimation of historical groundwater contam- inant distribution using the adjoint state method applied to geostatistical inverse mod- eling. Water Resources Research, 40(8):n/a–n/a, 2004. ISSN 1944-7973. W08302. E. M. Oblow. Sensitivity theory for reactor thermal-hydraulics problems. Nuclear Science and Engineering, 68(3):322–337, 1978. M. Panzeri, M. Riva, A. Guadagnini, and S.P. Neuman. Comparison of ensemble kalman filter groundwater-data assimilation methods based on stochastic moment equations and monte carlo simulation. Advances in Water Resources, 66:8 – 18, 2014. ISSN 0309-1708. Ce´cile Penland. A stochastic model of indopacific sea surface temperature anomalies.Physica D: Nonlinear Phenomena, 98(2):534 – 558, 1996. ISSN 0167-2789. F. Schweppe. Evaluation of likelihood functions for gaussian signals. IEEE Transactions on Information Theory, 11(1):61–70, Jan 1965. N.Z. Sun. Inverse Problems in Groundwater Modeling. Theory and Applications of Transport in Porous Media. Springer Netherlands, 2013. ISBN 9789401719704. N.Z. Sun and William W.-G. Yeh. Coupled inverse problems in groundwater modeling:1. sensitivity analysis and parameter identification. Water Resources Research, 26(10): 2507–2525, 1990. ISSN 1944-7973. P. Swerling. Parameter estimation for waveforms in additive gaussian noise. J. Soc. Indust. Appl. Math., 7(2):152–166., 1959. C. Torrence and G. P. Compo. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1):61–78, 1998. Christopher Torrence and Peter J. Webster. The annual cycle of persistence in the el nn˜o/southern oscillation. Quarterly Journal of the Royal Meteorological Society, 124 (550):1985–2004, 1998. ISSN 1477-870X. A.T. Watson, J.H. Seinfeld, G.R. Gavalas, and P.T. Woo. History matching in two-phase petroleum reservoirs. Society of Petroleum Engineers Journal, 20, 1980. N. Wiener. The extrapolation, interpolation and smoothing of stationary time series. [Cambridge]: Technology Press of the Massachusetts Institute ofTechnology, 1949. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68637 | - |
| dc.description.abstract | 參數推估在地下水模型當中有很重要的地位。當我們在建立地下水模型時，需要水文地質參數才能夠執行，但是由於土壤的異質性使得地下水參數推估有很高的不確定性。因此，本研究利用延伸卡曼濾波器來解決這樣的問題。延伸卡曼濾波器為一遞迴型的最佳化運算模式，可以處理非線性動態系統的推估問題。除此之外，由於卡曼濾波器的計算過程中，狀態轉換函數會需要耗費比較多的時間，因此，使用伴隨狀態法來增進計算效率。另外，當地下水問題中有考慮抽水補注的時候，加入頻率分析的方法，如小波分析及經驗正交函數分析，先用小波分析過濾出所要分析的頻率，再用經驗正交函數找出抽水補助的特徵。
本研究共有四個模擬試驗，前面三個是在局限含水層。第一個和第二個模擬試驗是用來驗證伴隨狀態法對計算效率的提升。第三個則是考慮抽水補注，當作其中需要推估的參數。第四個則是與其他三個不同，考慮在非侷限含水層中狀況。本研究提供了參數推估當中，結合多種數學方法的新思維。 | zh_TW |
| dc.description.abstract | Parameter estimation is a significant region in groundwater modeling. When constructing groundwater model, hydrogeological parameters are necessary. However, the observation data of parameters is not sufficient. Moreover, because of the heterogeneity of soil, parameter estimation contains high uncertainty. Therefore, Kalman Filter is applied to handle this issue. In addition, to improve the computational ability, Adjoint State Method replaces the conventional method while calculating State Transition Matrix in Kalman Filter process. Moreover, signal analysis method, such as Empirical Orthogonal Function (EOF) and Wavelet Analysis, can enhance the capability of Kalman Filter when dealing with problem containing sink/source. This study contain four simulation cases. The first case and the second case is a set of comparison which aims to validate that the Adjoint State Method can improve the efficiency of Kalman Filter. The third case contains the situation with sink/source. Frequency analysis methods are joined in this part. Different from another three cases, the fourth case is under the situation of unconfined aquifer.This study provides a new viewpoint which combine several methods to handle groundwater parameter estimation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:28:28Z (GMT). No. of bitstreams: 1 ntu-106-R04622021-1.pdf: 2690634 bytes, checksum: 4bbfcdce2bae8c2c94d369c464d16f3d (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 1 Introduction..........................1
1.1 MotivationandPurpose..........................1 1.2 ChapterDescription............................2 2 LiteratureReview..........................3 2.1 KalmanFilter................................3 2.2 AdjointStateMethod............................4 2.3 EmpiricalOrthogonalFunction.......................5 2.4 WaveletAnalysis..............................6 3 Methods..........................7 3.1 ExtendedKalmanFilter...........................8 3.2 DiscreteAdjointStateMethod.......................11 3.3 EmpiricalOrthogonalFunction.......................15 3.4 ContinuousWaveletTransform......................17 3.5 Methodology................................18 4 SimulationCase..........................20 4.1 ConfinedAquifer..............................23 4.1.1 CasewithoutSink/Source.....................23 4.1.2 CasewithSink/Source.......................34 4.2 UnconfinedAquifer.............................41 5 Discussion..........................50 6 ConclusionandRecommandation..........................51 6.1 Conclusion.................................51 6.2 Recommandation..............................51 7 Reference..........................52 | |
| dc.language.iso | en | |
| dc.subject | 地下水 | zh_TW |
| dc.subject | 參數推估 | zh_TW |
| dc.subject | 小波分析 | zh_TW |
| dc.subject | 延伸卡曼濾波器 | zh_TW |
| dc.subject | 伴隨狀態法 | zh_TW |
| dc.subject | 經驗正交函數 | zh_TW |
| dc.subject | groundwater | en |
| dc.subject | Empirical Orthogonal Function | en |
| dc.subject | Extended Kalman Filter | en |
| dc.subject | parameter estimation | en |
| dc.subject | Ajoint State Method | en |
| dc.subject | Wavelet Analysis | en |
| dc.title | 以伴隨狀態法及小波分析增進延伸卡曼濾波器對地下水參數推估之效率 | zh_TW |
| dc.title | Applying Adjoint State Method and Wavelet Analysis to Extended Kalman Filter to Enhance the Efficiency on Groundwater Parameter Estimation | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 張良正(Liang-Cheng Chang),陳主惠(Chu-Hui Chen),胡明哲(Ming-Che Hu) | |
| dc.subject.keyword | 伴隨狀態法,經驗正交函數,延伸卡曼濾波器,地下水,參數推估,小波分析, | zh_TW |
| dc.subject.keyword | Ajoint State Method,Empirical Orthogonal Function,Extended Kalman Filter,groundwater,parameter estimation,Wavelet Analysis, | en |
| dc.relation.page | 58 | |
| dc.identifier.doi | 10.6342/NTU201703765 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-08-18 | |
| 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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