Integration of artificial neural networks with conceptual models in rainfall-runoff modeling
Tài liệu tham khảo
2000, Artificial neural networks in hydrology. I: preliminary concepts, J. Hydr. Eng., 5, 124, 10.1061/(ASCE)1084-0699(2000)5:2(124)
2000, Artificial neural networks in hydrology. II: hydrologic applications, J. Hydrologic Engrg., 5, 115, 10.1061/(ASCE)1084-0699(2000)5:2(115)
Burnash, 1973
Cannon, 2002, Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural networks, J. Hydrol., 259, 136, 10.1016/S0022-1694(01)00581-9
Chen J.Y., 1998. Application of GIS in Conceptual Rainfall-Runoff Modeling. M.Sc thesis, Department of Engineering Hydrology, National University of Ireland, Galway, Republic of Ireland.
Crawford, N.H., Linsley, R.K., 1966. Digital Simulation in Hydrology: Stanford Watershed Model IV, Technical Report 39, Department of Civil Engineering, Stanford University, Stanford, CA.
Dawson, 1998, An artificial neural network approach to rainfall-runoff modeling, Hydr. Sci., 43, 47, 10.1080/02626669809492102
Dooge, 1977, Problems and methods of rainfall-runoff modeling, 71
Funahashi, 1989, On the approximate realization of continuous mappings by neural networks, Neural Networks, 2, 183, 10.1016/0893-6080(89)90003-8
Gautam, 2000, Runoff analysis in humid forest catchment with artificial neural network, J. Hydrol., 235, 117, 10.1016/S0022-1694(00)00268-7
Hornik, 1989, Multilayer feedforward networks are universal approximators, Neural Networks, 2, 359, 10.1016/0893-6080(89)90020-8
Hsu, 1995, Artificial neural network modeling of the rainfall-runoff process, Water Resour. Res., 31, 2517, 10.1029/95WR01955
Kitanidis, 1980, Adaptive filtering through detection of isolated transient errors in rainfall-runoff models, Water Resour. Res., 16, 740, 10.1029/WR016i004p00740
Kitanidis, 1980, Real-time forecasting with a conceptual hydrological model, Water Resour. Res., 16, 740, 10.1029/WR016i004p00740
Lee, 2002, Hybrid neural network modeling of a full-scale industrial wastewater treatment process, Biotechnol. Bioeng., 78, 670, 10.1002/bit.10247
Nash, 1970, River flow forecasting through conceptual models, part 1. A discussion of principles, J. Hydrol., 10, 282, 10.1016/0022-1694(70)90255-6
O'Connell, 1970, River flow forecasting through conceptual models. Part 2. The Brosna catchment at Ferbane, J. Hydrol., 10, 317, 10.1016/0022-1694(70)90221-0
O'Connor, K.M., 1997. Applied hydrology I-deterministic. Unpublished Lecture Notes. Department of Engineering Hydrology, National University of Ireland, Galway.
Rosenbrock, 1960, An automatic method for finding the greatest or least value of a function, Comput. J., 3, 175, 10.1093/comjnl/3.3.175
Sajikumar, 1999, A non-linear rainfall-runoff model using an artificial neural network, J. Hydrol., 216, 32, 10.1016/S0022-1694(98)00273-X
Schumann, 2000, Application of a geographic information system for conceptual rainfall-runoff modeling, J. Hydrol., 240, 45, 10.1016/S0022-1694(00)00312-7
Shamseldin, 1997, Application of a neural network technique to rainfall-runoff modeling, J. Hydrol., 199, 272, 10.1016/S0022-1694(96)03330-6
Smith, 1995, Neural-network models of rainfall-runoff process, J. Water Resour. Plng. Mgmt., ASCE, 4, 232
Spendy, 1962, Sequential application of simplex design in optimisation and evolutionary design, Technometrics, 4, 441, 10.2307/1266283
Sugawara, 1961, On the analysis of runoff structure about several Japanese rivers, Jap. J. Geophys., 2, 1
Sugawara, 1995
Tan, 1996, Application of an empirical infiltration quation in the SMAR conceptual model, J. Hydrol., 185, 275, 10.1016/0022-1694(95)02993-1
Tokar, 1999, Rainfall-runoff modeling using artificial neural network, J. Hydr. Eng., ASCE, 4, 232, 10.1061/(ASCE)1084-0699(1999)4:3(232)
Tokar, 2000, Precipitation-runoff modeling using artificial neural networks and concettual models, J. Hydr. Eng., ASCE, 5, 156, 10.1061/(ASCE)1084-0699(2000)5:2(156)
Van Can, 1997, An efficient model development strategy for bioprocesses based on neural networks in macroscopic balance, Biotechnol. Bioeng., 54, 549, 10.1002/(SICI)1097-0290(19970620)54:6<549::AID-BIT6>3.0.CO;2-J
Wang, 1991, The genetic algorithm and its application to calibrating conceptual rainfall-runoff models, Water Resour. Res., 27, 2367, 10.1029/91WR01305
Zhang, 2003, Geomorphology-based artifical neural networks (GANNs) for estimation of direct runoff over watersheds, J. Hydrol., 273, 18, 10.1016/S0022-1694(02)00313-X
Zhao, 1992, The Xinanjiang model applied in China, J. Hydrol., 135, 371
Zhao, 1995, The Xinanjiang model
Zhao, R.J., Zhang, Y.L., Fang, L.R., Liu, X.R., Zhang, Q.S., 1980. The Xinanjiang model, in Hydrological forecasting, proceedings of the Oxford symposium, IAHS. vol. 129, pp. 351–356.
Zhao, 1997, Modeling nutrient dynamics in sequencing batch reactor, J. Environ. Eng., 123, 311, 10.1061/(ASCE)0733-9372(1997)123:4(311)