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Volumn 17, Issue 3, 2012, Pages 394-404

Modeling of Suspended Sediment Concentration at Kasol in India Using ANN, Fuzzy Logic, and Decision Tree Algorithms

Author keywords

Bhakra reservoir; Fuzzy Logic; M5; Neural networks; REPTree; Suspended sediment concentration

Indexed keywords

AUTOCORRELATION FUNCTIONS; CROSS-CORRELATION FUNCTION; DECISION MAKERS; DECISION-TREE ALGORITHM; FIELD ENGINEERS; HIGH VARIABILITY; INPUT VECTOR; M5; M5 MODEL TREE; PIECE-WISE LINEAR FUNCTIONS; RADIAL BASIS FUNCTIONS; REPTREE; SEDIMENT CONCENTRATION; SEDIMENT LOADING; SOFTCOMPUTING TECHNIQUES; STATISTICAL PROPERTIES; SUSPENDED SEDIMENT CONCENTRATION; SUSPENDED SEDIMENT CONCENTRATIONS;

EID: 84859363621     PISSN: 10840699     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)HE.1943-5584.0000445     Document Type: Article
Times cited : (78)

References (60)
  • 1
    • 84855893978 scopus 로고    scopus 로고
    • Development of stage discharge rating curve using model tree and neural networks: An application to Peachtree Creek in Atlanta
    • ESAPEH, 0957-4174, 10.1016/j.eswa.2011.11.101.
    • Ajmera T.K. Goyal M.K. Development of stage discharge rating curve using model tree and neural networks: An application to Peachtree Creek in Atlanta. Expert Syst. Appl. 2012, 39(5):5702-5710. ESAPEH, 0957-4174, 10.1016/j.eswa.2011.11.101.
    • (2012) Expert Syst. Appl. , vol.39 , Issue.5 , pp. 5702-5710
    • Ajmera, T.K.1    Goyal, M.K.2
  • 2
    • 0034174280 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology-I: Preliminary concepts
    • ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2000)5:2(115), (a) .
    • Artificial neural networks in hydrology-I: Preliminary concepts. J. Hydrol. Eng. 2000, 5(2):115-123. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2000)5:2(115), (a).
    • (2000) J. Hydrol. Eng. , vol.5 , Issue.2 , pp. 115-123
  • 3
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology-II: Hydrologic applications
    • ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2000)5:2(124)
    • Artificial neural networks in hydrology-II: Hydrologic applications. J. Hydrol. Eng. 2000, 5(2):124-137. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology, JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2000)5:2(124), (b).
    • (2000) J. Hydrol. Eng. , vol.5 , Issue.2 , pp. 124-137
  • 4
    • 78049456545 scopus 로고    scopus 로고
    • Machine learning approach to predict sediment load-A case study
    • 1863-0650, 10.1002/clen.201000068.
    • Azamathulla H. Ghani A. Chang C.K. Hasan Z.A. Zakaria N.A. Machine learning approach to predict sediment load-A case study. Clean-Soil, Air, Water 2010, 38(10):969-976. 1863-0650, 10.1002/clen.201000068, .
    • (2010) Clean-Soil, Air, Water , vol.38 , Issue.10 , pp. 969-976
    • Azamathulla, H.1    Ghani, A.2    Chang, C.K.3    Hasan, Z.A.4    Zakaria, N.A.5
  • 5
    • 0026116468 scopus 로고
    • Orthogonal least squares learning algorithm for radial basis function networks
    • ITNNEP, 1045-9227, 10.1109/72.80341.
    • Chen S. Cowan C.F. N. Grant P.M. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans. Neural Network 1991, 2(2):302-309. ITNNEP, 1045-9227, 10.1109/72.80341.
    • (1991) IEEE Trans. Neural Network , vol.2 , Issue.2 , pp. 302-309
    • Chen, S.1    Cowan, C.F.N.2    Grant, P.M.3
  • 6
    • 84974743850 scopus 로고
    • Fuzzy model identification based on cluster estimation
    • JIFSE2, 1064-1246.
    • Chiu S. Fuzzy model identification based on cluster estimation. J. Intell. Fuzzy Sys. 1994, 2(3):267-278. JIFSE2, 1064-1246.
    • (1994) J. Intell. Fuzzy Sys. , vol.2 , Issue.3 , pp. 267-278
    • Chiu, S.1
  • 7
    • 0036171309 scopus 로고    scopus 로고
    • Suspended sediment estimation for rivers using artificial neural networks and sediment rating curves
    • EESCF5, 1092-8758.
    • Cigizoglu H.K. Suspended sediment estimation for rivers using artificial neural networks and sediment rating curves. Turk., J. Eng. Environ. Sci. 2002, 26(1):27-36. EESCF5, 1092-8758.
    • (2002) Turk., J. Eng. Environ. Sci. , vol.26 , Issue.1 , pp. 27-36
    • Cigizoglu, H.K.1
  • 8
    • 28944434082 scopus 로고    scopus 로고
    • Methods to improve the neural network performance in suspended sediment estimation
    • JHYDA7, 0022-1694, 10.1016/j.jhydrol.2005.05.019.
    • Cigizoglu H.K. Kisi O. Methods to improve the neural network performance in suspended sediment estimation. J. Hydrol. (Amsterdam) 2006, 317(3-4):221-228. JHYDA7, 0022-1694, 10.1016/j.jhydrol.2005.05.019.
    • (2006) J. Hydrol. (Amsterdam) , vol.317 , Issue.3-4 , pp. 221-228
    • Cigizoglu, H.K.1    Kisi, O.2
  • 9
    • 60549084178 scopus 로고    scopus 로고
    • Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data
    • JHYDA7, 0022-1694, 10.1016/j.jhydrol.2008.12.024.
    • Cobaner M. Unal B. Kisi O. Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data. J. Hydrol. (Amsterdam) 2009, 367(1-2):52-61. JHYDA7, 0022-1694, 10.1016/j.jhydrol.2008.12.024.
    • (2009) J. Hydrol. (Amsterdam) , vol.367 , Issue.1-2 , pp. 52-61
    • Cobaner, M.1    Unal, B.2    Kisi, O.3
  • 10
    • 84859316563 scopus 로고    scopus 로고
    • Human readable rule induction in medical data mining: A survey of existing algorithms
    • 10.1007/978-0-387-84814-3_79, Springer LNEE
    • Daud M.N. R. Corne D.W. Human readable rule induction in medical data mining: survey of existing algorithms. Proc., WSEAS European Computing Conf. 2007, 1:787-798. 10.1007/978-0-387-84814-3_79 Springer LNEE
    • (2007) Proc., WSEAS European Computing Conf. , vol.1 , pp. 787-798
    • Daud, M.N.R.1    Corne, D.W.2
  • 11
    • 60649110244 scopus 로고    scopus 로고
    • Investigation of internal functioning of the radial-basis-function neural network river flow forecasting models
    • JHYEFF, 1084-0699, 10.1061/(ASCE)1084-0699(2009)14:3(286).
    • Fernando D.A. K. Shamseldin A.Y. Investigation of internal functioning of the radial-basis-function neural network river flow forecasting models. J. Hydrol. Eng. 2009, 14(3):286-292. JHYEFF, 1084-0699, 10.1061/(ASCE)1084-0699(2009)14:3(286).
    • (2009) J. Hydrol. Eng. , vol.14 , Issue.3 , pp. 286-292
    • Fernando, D.A.K.1    Shamseldin, A.Y.2
  • 12
    • 34547804846 scopus 로고    scopus 로고
    • Dynamics of suspended sediment transport at field-scale drain channels of irrigation-dominated watersheds in the Sonoran Desert, southeastern California
    • HYPRE3, 0885-6087, 10.1002/hyp.6398.
    • Gao P. Pasternack G. Dynamics of suspended sediment transport at field-scale drain channels of irrigation-dominated watersheds in the Sonoran Desert, southeastern California. Hydrol. Process. 2007, 21(16):2081-2092. HYPRE3, 0885-6087, 10.1002/hyp.6398.
    • (2007) Hydrol. Process. , vol.21 , Issue.16 , pp. 2081-2092
    • Gao, P.1    Pasternack, G.2
  • 14
    • 79960055572 scopus 로고    scopus 로고
    • Analysis of mean monthly rainfall runoff data of Indian catchments using dimensionless variables by neural network
    • 2152-2197, 10.4236/jep.2010.12020 .
    • Goyal M.K. Ojha C.S. P. Analysis of mean monthly rainfall runoff data of Indian catchments using dimensionless variables by neural network. J. Environ. Protect. 2010, 1(2):155-171. 2152-2197, 10.4236/jep.2010.12020.
    • (2010) J. Environ. Protect. , vol.1 , Issue.2 , pp. 155-171
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 15
    • 84858256180 scopus 로고    scopus 로고
    • Downscaling of surface temperature for lake catchment in arid region in India using linear multiple regression and neural networks
    • IJCLEU, 0899-8418, 10.1002/joc.2286, in press.
    • Goyal M.K. Ojha C.S. P. Downscaling of surface temperature for lake catchment in arid region in India using linear multiple regression and neural networks. Int. J. Climatol. 2012, IJCLEU, 0899-8418, 10.1002/joc.2286, in press.
    • (2012) Int. J. Climatol.
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 16
    • 84859371833 scopus 로고    scopus 로고
    • An evaluation of decision tree algorithm as a downscaling tool: Application on a Lake Basin for an arid region in India
    • University of Guelph, ON, Canada.
    • Goyal M.K. Ojha C.S. P. Burn Donald H. An evaluation of decision tree algorithm as downscaling tool: Application on Lake Basin for an arid region in India. 10th Conf. Canadian Geophysical Union 2010 University of Guelph, ON, Canada.
    • (2010) 10th Conf. Canadian Geophysical Union
    • Goyal, M.K.1    Ojha, C.S.P.2    Burn Donald, H.3
  • 17
    • 84859315699 scopus 로고    scopus 로고
    • Downscaling of precipitation on a Lake Basin: Evaluation of rule and decision tree induction algorithms
    • in press.
    • Goyal M.K. Ojha C.S. P. Downscaling of precipitation on Lake Basin: Evaluation of rule and decision tree induction algorithms. Hydrol. Res. 2012b, 43. and in press.
    • (2012) Hydrol. Res. , vol.43
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 18
    • 79960059344 scopus 로고    scopus 로고
    • Estimation of scour downstream of a ski-jump bucket using support vector and m5 model tree
    • 10.1007/s11269-011-9801-6.
    • Goyal M.K. Ojha C.S. P. Estimation of scour downstream of ski-jump bucket using support vector and m5 model tree. Water Resour. Manage. 2011, 25(9):2177-2195. 10.1007/s11269-011-9801-6.
    • (2011) Water Resour. Manage. , vol.25 , Issue.9 , pp. 2177-2195
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 19
    • 0028543366 scopus 로고
    • Training feed forward networks with the Marquardt algorithm
    • ITNNEP, 1045-9227, 10.1109/72.329697.
    • Hagan M.T. Menhaj M.B. Training feed forward networks with the Marquardt algorithm. IEEE Trans. Neural Networks 1994, 5(6):989-993. ITNNEP, 1045-9227, 10.1109/72.329697.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.6 , pp. 989-993
    • Hagan, M.T.1    Menhaj, M.B.2
  • 20
    • 78649343954 scopus 로고    scopus 로고
    • Estimation of yield sediment using artificial neural network at basin scale
    • 2076-0841.
    • Haghizadeh A. Shui L.T. Goudarzi E. Estimation of yield sediment using artificial neural network at basin scale. Australian J. Basic Appl. Sci. 2010, 4(7):1668-1675. 2076-0841.
    • (2010) Australian J. Basic Appl. Sci. , vol.4 , Issue.7 , pp. 1668-1675
    • Haghizadeh, A.1    Shui, L.T.2    Goudarzi, E.3
  • 21
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff process
    • WRERAQ, 0043-1397, 10.1029/95WR01955.
    • Hsu K.-L. Gupta H.V. Sorooshian S. Artificial neural network modeling of the rainfall-runoff process. Water Resour. Res. 1995, 31(10):2517-2530. WRERAQ, 0043-1397, 10.1029/95WR01955.
    • (1995) Water Resour. Res. , vol.31 , Issue.10 , pp. 2517-2530
    • Hsu, K.-L.1    Gupta, H.V.2    Sorooshian, S.3
  • 22
    • 2442639370 scopus 로고    scopus 로고
    • Development of effective and efficient rainfall-runoff models using integration of deterministic, real-coded genetic algorithms and artificial neural network techniques
    • W04302, WRERAQ, 0043-1397, 10.1029/2003WR002355.
    • Jain A. Srinivasulu S. Development of effective and efficient rainfall-runoff models using integration of deterministic, real-coded genetic algorithms and artificial neural network techniques. Water Resour. Res. 2004, 40(4):W04302, 1-12. WRERAQ, 0043-1397, 10.1029/2003WR002355.
    • (2004) Water Resour. Res. , vol.40 , Issue.4 , pp. 1-12
    • Jain, A.1    Srinivasulu, S.2
  • 23
    • 0034746272 scopus 로고    scopus 로고
    • Development of integrated discharge and sediment rating relation using a Compound Neural Network
    • JHEND8, 0733-9429, 10.1061/(ASCE)0733-9429(2001)127:1(30).
    • Jain S.K. Development of integrated discharge and sediment rating relation using Compound Neural Network. J. Hydrol. Eng. 2001, 127(1):30-37. JHEND8, 0733-9429, 10.1061/(ASCE)0733-9429(2001)127:1(30).
    • (2001) J. Hydrol. Eng. , vol.127 , Issue.1 , pp. 30-37
    • Jain, S.K.1
  • 24
    • 39549114408 scopus 로고    scopus 로고
    • Development of integrated sediment rating curves using ANNs
    • JHEND8, 0733-9429, 10.1061/(ASCE)1084-0699(2008)13:3(124).
    • Jain S.K. Development of integrated sediment rating curves using ANNs. J. Hydrol. Eng. 2008, 13(3):124-131. JHEND8, 0733-9429, 10.1061/(ASCE)1084-0699(2008)13:3(124).
    • (2008) J. Hydrol. Eng. , vol.13 , Issue.3 , pp. 124-131
    • Jain, S.K.1
  • 25
    • 4444228763 scopus 로고    scopus 로고
    • Analysis of soil water retention data using artificial neural networks
    • JHEND8, 0733-9429, 10.1061/(ASCE)1084-0699(2004)9:5(415).
    • Jain S.K. Singh V.P. Genuchten M.T. V. Analysis of soil water retention data using artificial neural networks. J. Hydrol. Eng. 2004, 9(5):415-420. JHEND8, 0733-9429, 10.1061/(ASCE)1084-0699(2004)9:5(415).
    • (2004) J. Hydrol. Eng. , vol.9 , Issue.5 , pp. 415-420
    • Jain, S.K.1    Singh, V.P.2    Genuchten, M.T.V.3
  • 26
    • 10244249159 scopus 로고    scopus 로고
    • Multi-Layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation
    • HSJODN, 0262-6667, 10.1623/hysj.49.6.1025.55720.
    • Kisi O. Multi-Layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation. Hydrol. Sci. J. 2004, 49(6):1025-1040. HSJODN, 0262-6667, 10.1623/hysj.49.6.1025.55720.
    • (2004) Hydrol. Sci. J. , vol.49 , Issue.6 , pp. 1025-1040
    • Kisi, O.1
  • 27
    • 23044459648 scopus 로고    scopus 로고
    • Suspended sediment estimation using neuro-fuzzy and neural network approaches
    • HSJODN, 0262-6667, 10.1623/hysj.2005.50.4.683.
    • Kisi O. Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrol. Sci. J. 2005, 50(4):683-696. HSJODN, 0262-6667, 10.1623/hysj.2005.50.4.683.
    • (2005) Hydrol. Sci. J. , vol.50 , Issue.4 , pp. 683-696
    • Kisi, O.1
  • 28
    • 77954384995 scopus 로고    scopus 로고
    • River suspended sediment concentration modelling using a neural differential evolution approach
    • JHYDA7, 0022-1694, 10.1016/j.jhydrol.2010.06.003.
    • Kisi O. River suspended sediment concentration modelling using neural differential evolution approach. J. Hydrol. (Amsterdam) 2010, 389(1-2):227-235. JHYDA7, 0022-1694, 10.1016/j.jhydrol.2010.06.003.
    • (2010) J. Hydrol. (Amsterdam) , vol.389 , Issue.1-2 , pp. 227-235
    • Kisi, O.1
  • 29
    • 33845872549 scopus 로고    scopus 로고
    • River suspended sediment modelling using a fuzzy logic approach
    • HYPRE3, 0885-6087, 10.1002/hyp.6166.
    • Kisi O. Karahan M.E. Sen Z. River suspended sediment modelling using fuzzy logic approach. Hydrol. Process. 2006, 20(20):4351-4362. HYPRE3, 0885-6087, 10.1002/hyp.6166.
    • (2006) Hydrol. Process. , vol.20 , Issue.20 , pp. 4351-4362
    • Kisi, O.1    Karahan, M.E.2    Sen, Z.3
  • 31
    • 17544403172 scopus 로고    scopus 로고
    • Estimation of temporal variation of soil erosion and sediment yield using GIS
    • HSJODN, 0262-6667, 10.1080/02626660209492974.
    • Kothyari U.C. Jain M.K. Ranga Raju K.G. Estimation of temporal variation of soil erosion and sediment yield using GIS. Hydrol. Sci. J., IAHS 2002, 47(5):693-706. HSJODN, 0262-6667, 10.1080/02626660209492974.
    • (2002) Hydrol. Sci. J., IAHS , vol.47 , Issue.5 , pp. 693-706
    • Kothyari, U.C.1    Jain, M.K.2    Ranga Raju, K.G.3
  • 32
    • 34547743385 scopus 로고    scopus 로고
    • Deriving stage-discharge-sediment concentration relationships using Fuzzy logic
    • HSJODN, 0262-6667, 10.1623/hysj.52.4.793.
    • Lohani A.K. Goel N.K. Bhatia K.K. S. Deriving stage-discharge-sediment concentration relationships using Fuzzy logic. Hydrol. Sci. J. 2007, 52(4):793-807. HSJODN, 0262-6667, 10.1623/hysj.52.4.793.
    • (2007) Hydrol. Sci. J. , vol.52 , Issue.4 , pp. 793-807
    • Lohani, A.K.1    Goel, N.K.2    Bhatia, K.K.S.3
  • 33
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications
    • EMSOFT, 1364-8152, 10.1016/S1364-8152(99)00007-9.
    • Maier H.R. Dandy G.C. Neural networks for the prediction and forecasting of water resources variables: review of modelling issues and applications. Environ. Model. Software 2000, 15(1):101-124. EMSOFT, 1364-8152, 10.1016/S1364-8152(99)00007-9.
    • (2000) Environ. Model. Software , vol.15 , Issue.1 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 34
    • 0035888780 scopus 로고    scopus 로고
    • Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS Foundations of an expert system
    • ECMODT, 0304-3800, 10.1016/S0304-3800(01)00371-4.
    • Metternicht G. Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS Foundations of an expert system. Ecol. Model. 2001, 144(2-3):163-179. ECMODT, 0304-3800, 10.1016/S0304-3800(01)00371-4.
    • (2001) Ecol. Model. , vol.144 , Issue.2-3 , pp. 163-179
    • Metternicht, G.1
  • 35
    • 77952741865 scopus 로고    scopus 로고
    • Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine setting
    • GMLEDI, 0276-0460, 10.1007/s00367-009-0149-3.
    • Mianaei S.J. Keshavarzi A.R. Prediction of riverine suspended sediment discharge using fuzzy logic algorithms, and some implications for estuarine setting. Geo.-Mar. Lett. 2009, 30(1):35-45. GMLEDI, 0276-0460, 10.1007/s00367-009-0149-3.
    • (2009) Geo.-Mar. Lett. , vol.30 , Issue.1 , pp. 35-45
    • Mianaei, S.J.1    Keshavarzi, A.R.2
  • 36
    • 0030159380 scopus 로고    scopus 로고
    • Artificial neural networks as rainfall runoff models
    • HSJODN, 0262-6667, 10.1080/02626669609491511.
    • Minns A.W. Hall M.J. Artificial neural networks as rainfall runoff models. Hydrol. Sci. J. 1996, 41(3):399-418. HSJODN, 0262-6667, 10.1080/02626669609491511.
    • (1996) Hydrol. Sci. J. , vol.41 , Issue.3 , pp. 399-418
    • Minns, A.W.1    Hall, M.J.2
  • 37
    • 0036611003 scopus 로고    scopus 로고
    • Prediction of sediment load concentration in rivers using artificial neural networks
    • JHEND8, 0733-9429, 10.1061/(ASCE)0733-9429(2002)128:6(588).
    • Nagy H.M. Watanabe K. Hirano M. Prediction of sediment load concentration in rivers using artificial neural networks. J. Hydrol. Eng. 2002, 128(6):588-595. JHEND8, 0733-9429, 10.1061/(ASCE)0733-9429(2002)128:6(588).
    • (2002) J. Hydrol. Eng. , vol.128 , Issue.6 , pp. 588-595
    • Nagy, H.M.1    Watanabe, K.2    Hirano, M.3
  • 38
    • 0014776873 scopus 로고
    • River flow forecasting through conceptual models: 1. A discussion of principles
    • JHYDA7, 0022-1694, 10.1016/0022-1694(70)90255-6.
    • Nash J.E. Sutcliffe J.V. River flow forecasting through conceptual models: 1. discussion of principles. J. Hydrol. (Amsterdam) 1970, 10(3):282-290. JHYDA7, 0022-1694, 10.1016/0022-1694(70)90255-6.
    • (1970) J. Hydrol. (Amsterdam) , vol.10 , Issue.3 , pp. 282-290
    • Nash, J.E.1    Sutcliffe, J.V.2
  • 39
    • 36248929301 scopus 로고    scopus 로고
    • Applying Fuzzy logic and the point count system to select landfill sites
    • EMASDH, 0167-6369, 10.1007/s10661-007-9713-3.
    • Ojha C.S. P. Goyal M.K. Kumar S. Applying Fuzzy logic and the point count system to select landfill sites. Environ. Monit. Assess. 2007, 135(1-3):99-106. EMASDH, 0167-6369, 10.1007/s10661-007-9713-3.
    • (2007) Environ. Monit. Assess. , vol.135 , Issue.1-3 , pp. 99-106
    • Ojha, C.S.P.1    Goyal, M.K.2    Kumar, S.3
  • 40
    • 61849173511 scopus 로고    scopus 로고
    • Comparison of AnnAGNPS and SWAT model simulation results in USDA-CEAP agricultural watersheds in south-central Kansas
    • HYPRE3, 0885-6087, 10.1002/hyp.7174.
    • Parajuli P.B. Nelson N.O. Frees L.D. Mankin K.R. Comparison of AnnAGNPS and SWAT model simulation results in USDA-CEAP agricultural watersheds in south-central Kansas. Hydrol. Process. 2009, 23(5):748-763. HYPRE3, 0885-6087, 10.1002/hyp.7174.
    • (2009) Hydrol. Process. , vol.23 , Issue.5 , pp. 748-763
    • Parajuli, P.B.1    Nelson, N.O.2    Frees, L.D.3    Mankin, K.R.4
  • 42
    • 31444443313 scopus 로고    scopus 로고
    • Runoff and sediment yield modelling using artificial neural networks: Upper Siwane River, India
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2006)11:1(71).
    • Raghuwanshi N.S. Singh R. Reddy L.S. Runoff and sediment yield modelling using artificial neural networks: Upper Siwane River, India. J. Hydrol. Eng., 2006, 11(1):71-79. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2006)11:1(71).
    • (2006) J. Hydrol. Eng., , vol.11 , Issue.1 , pp. 71-79
    • Raghuwanshi, N.S.1    Singh, R.2    Reddy, L.S.3
  • 45
    • 16444365723 scopus 로고    scopus 로고
    • Rainfall-runoff modelling using artificial neural networks: Comparison of network types
    • HYPRE3, 0885-6087, 10.1002/hyp.5581.
    • Senthil Kumar A.R. Sudheer K.P. Jain S.K. Agarwal P.K. Rainfall-runoff modelling using artificial neural networks: Comparison of network types. Hydrol. Process. 2005, 19(6):1277-1291. HYPRE3, 0885-6087, 10.1002/hyp.5581.
    • (2005) Hydrol. Process. , vol.19 , Issue.6 , pp. 1277-1291
    • Senthil Kumar, A.R.1    Sudheer, K.P.2    Jain, S.K.3    Agarwal, P.K.4
  • 46
    • 0027870177 scopus 로고
    • An overview of reservoir sedimentation in some African river basins
    • IAHS, Institute of Hydrology, Wallingford, Oxfordshire, UK.
    • Shahin M.M. A. An overview of reservoir sedimentation in some African river basins. Sediment problems: Strategies for monitoring, prediction and control." Proc., Yokohama Symp. 1993, 217:93-100. ". No. IAHS, Institute of Hydrology, Wallingford, Oxfordshire, UK.
    • (1993) Sediment problems: Strategies for monitoring, prediction and control." Proc., Yokohama Symp. , vol.217 , pp. 93-100
    • Shahin, M.M.A.1
  • 47
    • 39549084921 scopus 로고    scopus 로고
    • Estimation of removal efficiency for settling basins using neural networks and support vector machines
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2008)13:3(146).
    • Singh K.K. Pal M. Ojha C.S. P. Singh V.P. Estimation of removal efficiency for settling basins using neural networks and support vector machines. J. Hydrol. Eng. 2008, 13(3):146-155. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2008)13:3(146).
    • (2008) J. Hydrol. Eng. , vol.13 , Issue.3 , pp. 146-155
    • Singh, K.K.1    Pal, M.2    Ojha, C.S.P.3    Singh, V.P.4
  • 48
    • 49249132565 scopus 로고    scopus 로고
    • Estimation of suspended sediment loads and delivery in an incised upland headwater catchment, south-eastern Australia
    • HYPRE3, 0885-6087, 10.1002/hyp.6898.
    • Smith H.G. Estimation of suspended sediment loads and delivery in an incised upland headwater catchment, south-eastern Australia. Hydrol. Process. 2008, 22(16):3135-3148. HYPRE3, 0885-6087, 10.1002/hyp.6898.
    • (2008) Hydrol. Process. , vol.22 , Issue.16 , pp. 3135-3148
    • Smith, H.G.1
  • 49
    • 57949116748 scopus 로고    scopus 로고
    • River flow prediction using an integrated approach
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2009)14:1(75).
    • Srinivasulu S. Jain A. River flow prediction using an integrated approach. J. Hydrol. Eng., 2009, 14(1):75-83. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2009)14:1(75).
    • (2009) J. Hydrol. Eng., , vol.14 , Issue.1 , pp. 75-83
    • Srinivasulu, S.1    Jain, A.2
  • 50
    • 0037197571 scopus 로고    scopus 로고
    • A data-driven algorithm for constructing artificial neural network rainfall-runoff models
    • HYPRE3, 0885-6087, 10.1002/hyp.554.
    • Sudheer K.P. Gosain A.K. Ramasastri K.S. data-driven algorithm for constructing artificial neural network rainfall-runoff models. Hydrol. Process. 2002, 16(6):1325-1330. HYPRE3, 0885-6087, 10.1002/hyp.554.
    • (2002) Hydrol. Process. , vol.16 , Issue.6 , pp. 1325-1330
    • Sudheer, K.P.1    Gosain, A.K.2    Ramasastri, K.S.3
  • 51
    • 0035338335 scopus 로고    scopus 로고
    • Modelling two-dimensional erosion process over infiltrating surfaces
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2001)6:3(259).
    • Tayfur G. Modelling two-dimensional erosion process over infiltrating surfaces. J. Hydrol. Eng. 2001, 6(3):259-262. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2001)6:3(259).
    • (2001) J. Hydrol. Eng. , vol.6 , Issue.3 , pp. 259-262
    • Tayfur, G.1
  • 52
    • 0036566519 scopus 로고    scopus 로고
    • Applicability of sediment transport capacity models for nonsteady state erosion from steep slopes
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2002)7:3(252).
    • Tayfur G. Applicability of sediment transport capacity models for nonsteady state erosion from steep slopes. J. Hydrol. Eng. 2002, 7(3):252-259. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(2002)7:3(252).
    • (2002) J. Hydrol. Eng. , vol.7 , Issue.3 , pp. 252-259
    • Tayfur, G.1
  • 53
    • 0242658864 scopus 로고    scopus 로고
    • Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces
    • AWREDI, 0309-1708, 10.1016/j.advwatres.2003.08.005.
    • Tayfur G. Ozdemir S. Singh V.P. Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces. Adv. Water Resour. 2003, 26(12):1249-1256. AWREDI, 0309-1708, 10.1016/j.advwatres.2003.08.005.
    • (2003) Adv. Water Resour. , vol.26 , Issue.12 , pp. 1249-1256
    • Tayfur, G.1    Ozdemir, S.2    Singh, V.P.3
  • 54
    • 0021564089 scopus 로고
    • Reservoir sedimentation in india-Its causes, control, and future course of action
    • WAINEL, 0250-8060, 10.1080/02508068408686525.
    • Tejwani K.G. Reservoir sedimentation in india-Its causes, control, and future course of action. Water Int. 1984, 9(4):150-154. WAINEL, 0250-8060, 10.1080/02508068408686525.
    • (1984) Water Int. , vol.9 , Issue.4 , pp. 150-154
    • Tejwani, K.G.1
  • 55
    • 84859341829 scopus 로고    scopus 로고
    • The MathWorks, 3 Apple Hill Drive, Natick, MA 01760-2098.
    • ANN Toolbox User's Guide 2001, The MathWorks, Apple Hill Drive, Natick, MA 01760-2098.
    • (2001) ANN Toolbox User's Guide
  • 56
    • 0031898654 scopus 로고    scopus 로고
    • River stage forecasting using artificial neural networks
    • JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(1998)3:1(26).
    • Thirumalaiah K. Deo M.C. River stage forecasting using artificial neural networks. J. Hydrol. Eng. 1998, 3(1):26-32. JHYEEF, 1084-0699, 10.1061/(ASCE)1084-0699(1998)3:1(26).
    • (1998) J. Hydrol. Eng. , vol.3 , Issue.1 , pp. 26-32
    • Thirumalaiah, K.1    Deo, M.C.2
  • 57
    • 53849113979 scopus 로고    scopus 로고
    • Multiobjective training of artificial neural networks for rainfall-runoff modelling
    • W08434, WRERAQ, 0043-1397.
    • Vos N.J. Rientjes T.H. M. Multiobjective training of artificial neural networks for rainfall-runoff modelling. Water Resour. Res. 2008, 44:W08434, 1-15. WRERAQ, 0043-1397.
    • (2008) Water Resour. Res. , vol.44 , pp. 1-15
    • Vos, N.J.1    Rientjes, T.H.M.2
  • 59
    • 34248666540 scopus 로고
    • Fuzzy sets
    • IETTAW, 0019-9958, 10.1016/S0019-9958(65)90241-X.
    • Zadeh L.A. Fuzzy sets. Inform. Control 1965, 8(3):338-353. IETTAW, 0019-9958, 10.1016/S0019-9958(65)90241-X.
    • (1965) Inform. Control , vol.8 , Issue.3 , pp. 338-353
    • Zadeh, L.A.1
  • 60
    • 0020843799 scopus 로고
    • The role of fuzzy logic in the management of uncertainty in expert systems
    • FSSYD8, 0165-0114, 10.1016/S0165-0114(83)80081-5.
    • Zadeh L.A. The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets Syst. 1983, 11(1-3):197-198. FSSYD8, 0165-0114, 10.1016/S0165-0114(83)80081-5.
    • (1983) Fuzzy Sets Syst. , vol.11 , Issue.1-3 , pp. 197-198
    • Zadeh, L.A.1


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