Data-driven modeling for river flood forecasting based on a piecewise linear ARX system identification
Tóm tắt
Từ khóa
Tài liệu tham khảo
Perrin, 2001, Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275, 10.1016/S0022-1694(00)00393-0
Elshorbagy, 2010, Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - part 2: application, Hydrol. Earth Syst. Sci., 14, 1943, 10.5194/hess-14-1943-2010
Asefa, 2006, Multi-time scale stream flow predictions: the support vector machines approach, J. Hydrol., 318, 7, 10.1016/j.jhydrol.2005.06.001
Siou, 2010, Flash floods forecasting in a karstic basin using neural networks: the case of the lez basin (south of france)
Nayak, 2004, A neuro-fuzzy computing technique for modeling hydrological time series, J. Hydrol., 291, 52, 10.1016/j.jhydrol.2003.12.010
Badrzadeh, 2017, Intermittent stream flow forecasting and modelling with hybrid wavelet neuro-fuzzy model, Hydrol. Res., 49, 27, 10.2166/nh.2017.163
Dariane, 2017, Streamflow forecasting by combining neural networks and fuzzy models using advanced methods of input variable selection, J. Hydroinformatics, 20, 520, 10.2166/hydro.2017.076
Chang, 2018, Rainfall-runoff modelling using a self-reliant fuzzy inference network with flexible structure, J. Hydrol., 564, 1179, 10.1016/j.jhydrol.2018.07.074
Young, 1986, Time series methods and recursive estimation in hydrological systems analysis, 129
Tóth, 2007, Discrete time lpv i/o and state space representations, differences of behavior and pitfalls of interpolation, Proc. of the European Control Conf., Kos, Greece, 5418
Previdi, 2009, Identification of parametrically-varying models for the rainfall-runoff relationship in urban drainage networks, 42, 1768
Laurain, 2010, Identification de modèles LPV : application à la modélisation pluie/débit d’un bassin versant viticole
Duviella, 2012, Predictive Black-Box Modeling Approaches for Flow Forecasting of the Liane River.
Ljung, 1999
Nash, 1970, River flow forecasting through conceptual models part i: a discussion of principles, J. Hydrol., 10, 282, 10.1016/0022-1694(70)90255-6
Perrin, 2003, Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275, 10.1016/S0022-1694(03)00225-7
Edijatno, 1989, Un modèle pluie-débit journalier à trois paramètres, La Houille Blanche, 2, 113, 10.1051/lhb/1989007
Edijatno, 1999, GR3J: a daily watershed model with three free parameters, Hydrol. Sci. J., 44, 263, 10.1080/02626669909492221
Bourgin, 2014, Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting, J. Hydrol., 519, 2775, 10.1016/j.jhydrol.2014.07.054
Ficchi, 2017
Dakhlaoui, 2017, Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern tunisia, J. Hydrol., 550, 201, 10.1016/j.jhydrol.2017.04.032
Bastin, 2009, Online river flow forecasting with hydromax : successes and challenges after twelve years of experience
Sjoberg, 1995, Nonlinear black-box modeling in system identification: a unified overview, Automatica, 31, 1691, 10.1016/0005-1098(95)00120-8
Paoletti, 2007, Identification of hybrid systems a tutorial, Eur. J. Control, 13, 242, 10.3166/ejc.13.242-260
Vidal, 2003, An algebraic geometric approach to the identification of a class of linear hybrid systems, 1, 167
Vidal, 2004, Identification of PWARX hybrid models with unknown and possibly different orders, 1, 547
Juloski, 2005, A bayesian approach to identification of hybrid systems, IEEE Trans. Autom. Control, 50, 1520, 10.1109/TAC.2005.856649
Bemporad, 2005, A bounded-error approach to piecewise affine system identification, IEEE Trans. Autom. Control, 50, 1567, 10.1109/TAC.2005.856667
Ferrari-Trecate, 2003, A clustering technique for the identification of piecewise affine systems, Automatica, 39(2), 205, 10.1016/S0005-1098(02)00224-8
Lauer, 2014, Piecewise smooth system identification in reproducing kernel hilbert space, 6498
Boukharouba, 2009, Identification of piecewise affine systems based on Dempster-Shafer theory, 1662
Lauer, 2011, A continuous optimization framework for hybrid system identification, Automatica, 47, 608, 10.1016/j.automatica.2011.01.020
Bako, 2014, Subspace clustering through parametric representation and sparse optimization, IEEE Signal Process. Lett., 21, 356, 10.1109/LSP.2014.2303122
Kersting, 2017, Recursive estimation in piecewise affine systems using parameter identifiers and concurrent learning, Int. J. Control, 0, 1
Bako, 2011, A recursive identification algorithm for switched linear/affine models, Nonlinear Anal., 5, 242
Breschi, 2016, Identification of hybrid and linear parameter varying models via recursive piecewise affine regression and discrimination, 2632
Breschi, 2016, Piecewise affine regression via recursive multiple least squares and multicategory discrimination, Automatica, 73, 155, 10.1016/j.automatica.2016.07.016
Shafer, 1976
Denoeux, 1995, A k-nearest neighbor classification rule based on dempster-shafer theory, IEEE Trans. Syst. Man. Cybern., 25, 804, 10.1109/21.376493
Hadid, 2017, Data assignment and parameter adaptation for switched LPV system estimation, 4564
Vapnik, 1995
Bredensteiner, 1999, Multicategory classification by support vector machines, Comput. Optim. Appl., 12, 53, 10.1023/A:1008663629662
Ohlsson, 2013, Identification of switched linear regression models using sum-of-norms regularization, Automatica, 49, 1045, 10.1016/j.automatica.2013.01.031
http://www.hydro.eaufrance.fr, (2019).
Norbiato, 2008, Flash flood warning based on rainfall thresholds and soil moisture conditions: an assessment for gauged and ungauged basins, J. Hydrol., 362, 274, 10.1016/j.jhydrol.2008.08.023
Kong, 2015, Wind speed prediction using reduced support vector machines with feature selection, Neurocomputing, 169, 449, 10.1016/j.neucom.2014.09.090
Hay, 1988, The derivation of global estimates from a confusion matrix, Int. J. Remote Sens., 9, 1395, 10.1080/01431168808954945
Sammut, 2011
Young, 2003, Top-down and data-based mechanistic modelling of rainfall-flow dynamics at the catchment scale, Hydrol. Processes, 17, 2195, 10.1002/hyp.1328
Levenberg, 1944, A method for the solution of certain non-linear problems in least squares, Q. Appl. Math., 2, 164, 10.1090/qam/10666
Marquardt, 1963, An algorithm for least-squares estimation of nonlinear parameters, J. Soc. Ind. Appl. Math., 11, 431, 10.1137/0111030
