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Volumn 28, Issue 7, 2014, Pages 1991-2003

Modeling of Sediment Yield Prediction Using M5 Model Tree Algorithm and Wavelet Regression

Author keywords

Discrete wavelet transform; Forecast; M5 model tree; Regression; Streamflow

Indexed keywords

DECISION TREES; DISCRETE WAVELET TRANSFORMS; FORECASTING; MEAN SQUARE ERROR; REGRESSION ANALYSIS; SEDIMENTS; SOFT COMPUTING; STREAM FLOW; TREES (MATHEMATICS); WATER RESOURCES; WATERSHEDS;

EID: 84899975429     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-014-0590-6     Document Type: Article
Times cited : (81)

References (61)
  • 1
    • 84855849356 scopus 로고    scopus 로고
    • Forecasting of runoff and sediment yield using artificial neural networks
    • Agarwal A, Rai RK, Upadhyay A (2009), Forecasting of runoff and sediment yield using artificial neural networks. Journal Water Resource and Protection 1: 368-375.
    • (2009) Journal Water Resource and Protection , vol.1 , pp. 368-375
    • Agarwal, A.1    Rai, R.K.2    Upadhyay, A.3
  • 2
    • 84855893978 scopus 로고    scopus 로고
    • Development of stage discharge rating curve using model tree and neural networks: an application to Peachtree Creek in Atlanta
    • 5702-5710
    • Ajmera TK, Goyal MK (2012) Development of stage discharge rating curve using model tree and neural networks: an application to Peachtree Creek in Atlanta. Expert Syst Appl 39(5): 5702-5710.
    • (2012) Expert Syst Appl , vol.39 , Issue.5
    • Ajmera, T.K.1    Goyal, M.K.2
  • 4
    • 39849091610 scopus 로고    scopus 로고
    • A genetic programming approach to suspended sediment modeling
    • Ayteek A, Kisi Ö (2008) A genetic programming approach to suspended sediment modeling. J Hydrol 351: 288-298.
    • (2008) J Hydrol , vol.351 , pp. 288-298
    • Ayteek, A.1    Kisi, Ö.2
  • 5
    • 12144264770 scopus 로고    scopus 로고
    • Neural networks and M5 model trees in modelling water level-discharge relationship
    • Bhattacharya B, Solomatine DP (2005) Neural networks and M5 model trees in modelling water level-discharge relationship. Neurocomputing 63: 381-396.
    • (2005) Neurocomputing , vol.63 , pp. 381-396
    • Bhattacharya, B.1    Solomatine, D.P.2
  • 6
    • 49449098130 scopus 로고    scopus 로고
    • Levenberg-Marquardt algorithm for karachi stock exchange share rates forecasting
    • Burney SMA, Jilani TA, Ardil C (2005) Levenberg-Marquardt algorithm for karachi stock exchange share rates forecasting. World Acad Sci Eng Technol 3: 171-176.
    • (2005) World Acad Sci Eng Technol , vol.3 , pp. 171-176
    • Burney, S.M.A.1    Jilani, T.A.2    Ardil, C.3
  • 7
    • 0021547622 scopus 로고
    • Rainfall-runoff-sediment yield relation by stochastic modelling
    • Caroni E, Singh VP, Ubertini L (1984) Rainfall-runoff-sediment yield relation by stochastic modelling. Hydrol Sci J 29(2): 203-218.
    • (1984) Hydrol Sci J , vol.29 , Issue.2 , pp. 203-218
    • Caroni, E.1    Singh, V.P.2    Ubertini, L.3
  • 8
    • 84864809578 scopus 로고    scopus 로고
    • Wavelet-based multi-scale entropy analysis of complex rainfall time series
    • doi:10.3390/e13010241
    • Chou C-M (2011) Wavelet-based multi-scale entropy analysis of complex rainfall time series. Entropy 13: 241-253. doi: 10. 3390/e13010241.
    • (2011) Entropy , vol.13 , pp. 241-253
    • Chou, C.-M.1
  • 9
    • 0036171309 scopus 로고    scopus 로고
    • Suspended sediment estimation for rivers using Artificial Neural Networks and Sediment Rating Curves
    • Cigizoglu HK (2002) Suspended sediment estimation for rivers using Artificial Neural Networks and Sediment Rating Curves. Turk J Eng Environ Sci 26: 27-36.
    • (2002) Turk J Eng Environ Sci , vol.26 , pp. 27-36
    • Cigizoglu, H.K.1
  • 10
    • 28944434082 scopus 로고    scopus 로고
    • Methods to improve the neural network performance in suspended sediment estimation
    • Cigizoglu HK, Kisi O (2006) Methods to improve the neural network performance in suspended sediment estimation. J Hydrol 317: 221-228.
    • (2006) J Hydrol , vol.317 , pp. 221-228
    • Cigizoglu, H.K.1    Kisi, O.2
  • 11
    • 60549084178 scopus 로고    scopus 로고
    • Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data
    • Cobaner M, Unal B, Kisi O (2009) Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data. J Hydrol 367: 52-61.
    • (2009) J Hydrol , vol.367 , pp. 52-61
    • Cobaner, M.1    Unal, B.2    Kisi, O.3
  • 12
    • 2042453329 scopus 로고    scopus 로고
    • Wavelet analysis of variability in annual Canadian streamflows
    • W03105
    • Coulibaly P, Burn HD (2004) Wavelet analysis of variability in annual Canadian streamflows. Water Resour Res 40, W03105.
    • (2004) Water Resour Res , vol.40
    • Coulibaly, P.1    Burn, H.D.2
  • 13
    • 60649110244 scopus 로고    scopus 로고
    • Investigation of internal functioning of the radial-basis-function neural network river flow forecasting models
    • Fernando DAK, Shamseldin AY (2009) "Investigation of internal functioning of the radial-basis-function neural network river flow forecasting models." J Hydrol Eng 14(3): 286-292.
    • (2009) J Hydrol Eng , vol.14 , Issue.3 , pp. 286-292
    • Fernando, D.A.K.1    Shamseldin, A.Y.2
  • 14
    • 84896266751 scopus 로고    scopus 로고
    • Evaluation of rule and decision tree induction algorithms for generating climate change scenarios for temperature and pan evaporation on a Lake Basin
    • 10. 1061/(ASCE)HE. 1943-5584. 0000615
    • Goyal MK, Ojha CSP (2014) Evaluation of rule and decision tree induction algorithms for generating climate change scenarios for temperature and pan evaporation on a Lake Basin. ASCE J Hydrol Eng 10. 1061/(ASCE)HE. 1943-5584. 0000615.
    • (2014) ASCE J Hydrol Eng
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 15
    • 0000562670 scopus 로고
    • Decomposition of hardy functions into square integrable wavelets of constant shape
    • Grossman A, Morlet J (1984) Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM J Math Anal 15: 732-736.
    • (1984) SIAM J Math Anal , vol.15 , pp. 732-736
    • Grossman, A.1    Morlet, J.2
  • 16
    • 78649343954 scopus 로고    scopus 로고
    • Estimation of yield sediment using artificial neural network at basin scale
    • Haghizadeh A, Shui LT, Goudarzi E (2010) Estimation of yield sediment using artificial neural network at basin scale. Aust J Basic Appl Sci 4(7): 1668-1675.
    • (2010) Aust J Basic Appl Sci , vol.4 , Issue.7 , pp. 1668-1675
    • Haghizadeh, A.1    Shui, L.T.2    Goudarzi, E.3
  • 17
    • 84896503896 scopus 로고    scopus 로고
    • Using artificial neural network to estimate sediment load in Ungauged catchments of the Tonle Sap River Basin, Cambodia
    • Heng S, Suetsugi T (2013) Using artificial neural network to estimate sediment load in Ungauged catchments of the Tonle Sap River Basin, Cambodia. J Water Resour Prot 5(2): 111-123.
    • (2013) J Water Resour Prot , vol.5 , Issue.2 , pp. 111-123
    • Heng, S.1    Suetsugi, T.2
  • 18
    • 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
    • Jain A, Srinivasulu S (2004). "Development of effective and efficient rainfall-runoff models using integration of deterministic, real-coded genetic algorithms and artificial neural network techniques." Water Resour Res 40(4): W04302, 1-12.
    • (2004) Water Resour Res , vol.40 , Issue.4 , pp. 1-12
    • Jain, A.1    Srinivasulu, S.2
  • 19
    • 10244249159 scopus 로고    scopus 로고
    • Multi-Layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation
    • Kisi O (2004) Multi-Layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation. Hydrol Sci J 49(6): 1025-1040.
    • (2004) Hydrol Sci J , vol.49 , Issue.6 , pp. 1025-1040
    • Kisi, O.1
  • 20
    • 23044459648 scopus 로고    scopus 로고
    • Suspended sediment estimation using neuro-fuzzy and neural network approaches
    • Kisi O (2005) Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrol Sci J 50(4): 683-696.
    • (2005) Hydrol Sci J , vol.50 , Issue.4 , pp. 683-696
    • Kisi, O.1
  • 21
    • 71649094330 scopus 로고    scopus 로고
    • Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting
    • Kisi O (2009) Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting. Hydrol Process 23: 3583-3597.
    • (2009) Hydrol Process , vol.23 , pp. 3583-3597
    • Kisi, O.1
  • 22
    • 78751591071 scopus 로고    scopus 로고
    • Wavelet regression model as an alternative to neural networks for river stage forecasting
    • Kisi O (2011) Wavelet regression model as an alternative to neural networks for river stage forecasting. Water Resour Manag 25(2): 579-600.
    • (2011) Water Resour Manag , vol.25 , Issue.2 , pp. 579-600
    • Kisi, O.1
  • 23
    • 84857685424 scopus 로고    scopus 로고
    • Modeling discharge-sediment relationship using neural networks with artificial bee colony algorithm
    • Kisi Ö, Ozkan C, Akay B (2012) Modeling discharge-sediment relationship using neural networks with artificial bee colony algorithm. J Hydrol 428-429: 94-103.
    • (2012) J Hydrol , vol.428-429 , pp. 94-103
    • Kisi, Ö.1    Ozkan, C.2    Akay, B.3
  • 24
    • 84887638501 scopus 로고    scopus 로고
    • Monthly rainfall prediction using wavelet regression and neural network: An analysis of 1901-2002 data, Assam, India
    • Springer. doi: 10. 1007/s00704-013-1029-3
    • Goyal MK (2014) "Monthly rainfall prediction using wavelet regression and neural network: An analysis of 1901-2002 data, Assam, India", Theoretical and Applied Climatology, Springer. doi: 10. 1007/s00704-013-1029-3.
    • (2014) Theoretical and Applied Climatology
    • Goyal, M.K.1
  • 25
    • 79960059344 scopus 로고    scopus 로고
    • Estimation of scour downstream of a ski-jump bucket using support vector and M5 model tree
    • Goyal MK, Ojha CSP (2011) Estimation of scour downstream of a ski-jump bucket using support vector and M5 model tree. Water Resour Manag 25: 2177-2195.
    • (2011) Water Resour Manag , vol.25 , pp. 2177-2195
    • Goyal, M.K.1    Ojha, C.S.P.2
  • 26
    • 84898464831 scopus 로고    scopus 로고
    • Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS
    • doi: 10. 1016/j. eswa. 2014. 02. 047
    • Goyal MK, Bharti B, Quilty J, Adamowski J, Pandey A (2014) Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS, Expert Systems With Applications. doi: 10. 1016/j. eswa. 2014. 02. 047.
    • (2014) Expert Systems With Applications
    • Goyal, M.K.1    Bharti, B.2    Quilty, J.3    Adamowski, J.4    Pandey, A.5
  • 27
    • 0034610444 scopus 로고    scopus 로고
    • Rainfall-runoff relations for karstic springs. Part II. Continuous wavelet and discrete orthogonal multiresolution analyses
    • Labat D, Ababou R, Mangin A (2000) Rainfall-runoff relations for karstic springs. Part II. Continuous wavelet and discrete orthogonal multiresolution analyses. J Hydrol 238(3-4): 149-178.
    • (2000) J Hydrol , vol.238 , Issue.3-4 , pp. 149-178
    • Labat, D.1    Ababou, R.2    Mangin, A.3
  • 28
    • 28444486059 scopus 로고    scopus 로고
    • Recent advances in wavelet analyses. Part 2- Amazon, Parana, Orinoco and Congo discharges time scale variability
    • Labat D, Ronchail J, Guyot JL (2005) Recent advances in wavelet analyses. Part 2- Amazon, Parana, Orinoco and Congo discharges time scale variability. J Hydrol 314(1-4): 289-311.
    • (2005) J Hydrol , vol.314 , Issue.1-4 , pp. 289-311
    • Labat, D.1    Ronchail, J.2    Guyot, J.L.3
  • 29
    • 34547743385 scopus 로고    scopus 로고
    • Deriving stage-discharge-sediment concentration relationships using Fuzzy logic
    • Lohani AK, Goel NK, Bhatia KKS (2007) Deriving stage-discharge-sediment concentration relationships using Fuzzy logic. Hydrol Sci J 52(4): 793-807.
    • (2007) Hydrol Sci J , vol.52 , Issue.4 , pp. 793-807
    • Lohani, A.K.1    Goel, N.K.2    Bhatia, K.K.S.3
  • 30
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications
    • Maier HR, Dandy GC (2000) Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environ Model Softw 15: 101-124.
    • (2000) Environ Model Softw , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 31
    • 0024700097 scopus 로고
    • A theory of multiresolution signal decomposition: the wavelet representation
    • Mallat S, (1989) A theory of multiresolution signal decomposition: the wavelet representation, IEEE Trans. Pattern Anal, Machine Intell.
    • (1989) IEEE Trans. Pattern Anal, Machine Intell
    • Mallat, S.1
  • 32
    • 0030159380 scopus 로고    scopus 로고
    • Artificial neural networks as rainfall runoff models
    • Minns AW, Hall MJ (1996) Artificial neural networks as rainfall runoff models. Hydrol Sci J 41(3): 399-418.
    • (1996) Hydrol Sci J , vol.41 , Issue.3 , pp. 399-418
    • Minns, A.W.1    Hall, M.J.2
  • 33
    • 67650293317 scopus 로고    scopus 로고
    • Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed
    • doi:10.1002/hyp.7136
    • Mutlu E, Chaubey I, Hexmoor H, Bajwa SG (2008) Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed. Hydrol Process. doi: 10. 1002/hyp. 7136.
    • (2008) Hydrol Process
    • Mutlu, E.1    Chaubey, I.2    Hexmoor, H.3    Bajwa, S.G.4
  • 34
    • 0036611003 scopus 로고    scopus 로고
    • Prediction of sediment load concentration in rivers using artificial neural networks
    • Nagy HM, Watanabe K, Hirano M (2002) Prediction of sediment load concentration in rivers using artificial neural networks. J Hydrol Eng 128(6): 588-595.
    • (2002) J Hydrol Eng , vol.128 , Issue.6 , pp. 588-595
    • Nagy, H.M.1    Watanabe, K.2    Hirano, M.3
  • 35
    • 33751399443 scopus 로고    scopus 로고
    • Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region
    • (Turkey)
    • Partal T, Kucuk M (2006) Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region. Phys Chem Earth 31: 1189-1200 (Turkey).
    • (2006) Phys Chem Earth , vol.31 , pp. 1189-1200
    • Partal, T.1    Kucuk, M.2
  • 38
    • 31444443313 scopus 로고    scopus 로고
    • Runoff and sediment yield modelling using Artificial Neural Networks: Upper Siwane River, India
    • Raghuwanshi NS, Singh R, Reddy LS (2006) Runoff and sediment yield modelling using Artificial Neural Networks: Upper Siwane River, India. J Hydrol Eng ASCE 11(1): 71-79.
    • (2006) J Hydrol Eng ASCE , vol.11 , Issue.1 , pp. 71-79
    • Raghuwanshi, N.S.1    Singh, R.2    Reddy, L.S.3
  • 39
    • 14744271316 scopus 로고    scopus 로고
    • Theme paper on "Water: vision 2050
    • Roorkee
    • Reddy MS (1999) Theme paper on "Water: vision 2050. Indian Water Resources Soc. Roorkee pp. 51-53.
    • (1999) Indian Water Resources Soc , pp. 51-53
    • Reddy, M.S.1
  • 40
    • 4444331199 scopus 로고    scopus 로고
    • Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings
    • Rosso OA, Figliola A, Creso J, Serrano E (2004) Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings. Med Biol Eng Comput 42(4): 516-523.
    • (2004) Med Biol Eng Comput , vol.42 , Issue.4 , pp. 516-523
    • Rosso, O.A.1    Figliola, A.2    Creso, J.3    Serrano, E.4
  • 41
    • 0033535432 scopus 로고    scopus 로고
    • A non-linear rainfall-runoff model using an artificial neural network
    • Sajikumar S, Thandaveswara BS (1999) A non-linear rainfall-runoff model using an artificial neural network. J Hydrol 216: 32-55.
    • (1999) J Hydrol , vol.216 , pp. 32-55
    • Sajikumar, S.1    Thandaveswara, B.S.2
  • 43
    • 84899923662 scopus 로고    scopus 로고
    • Analysis of precipitation time series of urban centers of Northeastern Brazil using wavelet transform
    • Santos CAG, Freire FKMM (2012) Analysis of precipitation time series of urban centers of Northeastern Brazil using wavelet transform. World Acad Sci Eng Technol 67: 845-850.
    • (2012) World Acad Sci Eng Technol , vol.67 , pp. 845-850
    • Santos, C.A.G.1    Freire, F.K.M.M.2
  • 44
    • 16444365723 scopus 로고    scopus 로고
    • Rainfall-runoff modelling using artificial neural networks: comparison of network types
    • Senthil Kumar AR, Sudheer KP, Jain SK, Agarwal PK (2005) Rainfall-runoff modelling using artificial neural networks: comparison of network types. Hydrol Process 19: 1277-1291.
    • (2005) Hydrol Process , vol.19 , pp. 1277-1291
    • Senthil Kumar, A.R.1    Sudheer, K.P.2    Jain, S.K.3    Agarwal, P.K.4
  • 45
    • 84859363621 scopus 로고    scopus 로고
    • Modelling of suspended sediment concentration at Kasol in India using ANN, fuzzy logic and decision tree algorithms
    • Senthil kumar AR, Ojha CSP, Goyal MK, Singh RD, Swamee PK (2012) Modelling of suspended sediment concentration at Kasol in India using ANN, fuzzy logic and decision tree algorithms. ASCE's J Hydrol Eng 17(3): 394-404.
    • (2012) ASCE's J Hydrol Eng , vol.17 , Issue.3 , pp. 394-404
    • Senthil Kumar, A.R.1    Ojha, C.S.P.2    Goyal, M.K.3    Singh, R.D.4    Swamee, P.K.5
  • 47
    • 33645987256 scopus 로고    scopus 로고
    • Machine learning approaches for estimation of prediction interval for the model output
    • Shrestha DL, Solomatine DP (2006) Machine learning approaches for estimation of prediction interval for the model output. Neural Netw 19(2): 225-235.
    • (2006) Neural Netw , vol.19 , Issue.2 , pp. 225-235
    • Shrestha, D.L.1    Solomatine, D.P.2
  • 48
    • 84876838740 scopus 로고    scopus 로고
    • Comparison of artificial neural network models for sediment yield prediction at single Gauging Station of Watershed in Eastern India
    • Singh A, Imtiyaz M, Isaac RK, Denis DM (2013) Comparison of artificial neural network models for sediment yield prediction at single Gauging Station of Watershed in Eastern India. J Hydrol Eng 18(1): 115-120.
    • (2013) J Hydrol Eng , vol.18 , Issue.1 , pp. 115-120
    • Singh, A.1    Imtiyaz, M.2    Isaac, R.K.3    Denis, D.M.4
  • 49
    • 0037197571 scopus 로고    scopus 로고
    • A data-driven algorithm for constructing artificial neural network rainfall-runoff models
    • Sudheer KP, Gosain AK, Ramasastri KS (2002) A data-driven algorithm for constructing artificial neural network rainfall-runoff models. Hydrol Process 16: 1325-1330.
    • (2002) Hydrol Process , vol.16 , pp. 1325-1330
    • Sudheer, K.P.1    Gosain, A.K.2    Ramasastri, K.S.3
  • 50
    • 0242658864 scopus 로고    scopus 로고
    • Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces
    • Tayfur G, Ozdemir S, Singh VP (2003) Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces. Adv Water Resour 26: 1249-1256.
    • (2003) Adv Water Resour , vol.26 , pp. 1249-1256
    • Tayfur, G.1    Ozdemir, S.2    Singh, V.P.3
  • 51
    • 0031898654 scopus 로고    scopus 로고
    • River stage forecasting using artificial neural networks
    • Thirumalaiah K, Deo MC (1998) River stage forecasting using artificial neural networks. J Hydrol Eng 3(1): 26-32.
    • (1998) J Hydrol Eng , vol.3 , Issue.1 , pp. 26-32
    • Thirumalaiah, K.1    Deo, M.C.2
  • 52
    • 0034174397 scopus 로고    scopus 로고
    • Precipitation-runoff model-ling using artificial neural networks and conceptual mod-els
    • Tokar AS, Markus M (2000) "Precipitation-runoff model-ling using artificial neural networks and conceptual mod-els," J Hydrol Eng 5(2): 156-161.
    • (2000) J Hydrol Eng , vol.5 , Issue.2 , pp. 156-161
    • Tokar, A.S.1    Markus, M.2
  • 55
    • 76549088933 scopus 로고    scopus 로고
    • Neural networks approaches for modelling river suspended sediment concentration due to tropical storms
    • Wang YM, Kerh T, Traore S (2009) Neural networks approaches for modelling river suspended sediment concentration due to tropical storms. Global Nest J 11(4): 457-466.
    • (2009) Global Nest J , vol.11 , Issue.4 , pp. 457-466
    • Wang, Y.M.1    Kerh, T.2    Traore, S.3
  • 56
    • 33845543385 scopus 로고    scopus 로고
    • Wavelet network model and its application to the prediction of hydrology
    • Wang D, Ding J (2003) Wavelet network model and its application to the prediction of hydrology. Nat Sci 1(1): 67-71.
    • (2003) Nat Sci , vol.1 , Issue.1 , pp. 67-71
    • Wang, D.1    Ding, J.2
  • 58
    • 77953485028 scopus 로고    scopus 로고
    • A comparative study on prediction of sediment yield in the Euphrates Basin
    • Yenigün K, Mahmut B, Reşit G, Mehmet M (2010) A comparative study on prediction of sediment yield in the Euphrates Basin. Int J Phys Sci 5(5): 518-534.
    • (2010) Int J Phys Sci , vol.5 , Issue.5 , pp. 518-534
    • Yenigün, K.1    Mahmut, B.2    Reşit, G.3    Mehmet, M.4
  • 60
    • 0037466126 scopus 로고    scopus 로고
    • Geomorphology-based artificial neural networks (GANNs) for estimation of direction runoff over watersheds
    • Zhang B, Govindaraju RS (2003) Geomorphology-based artificial neural networks (GANNs) for estimation of direction runoff over watersheds. J Hydrol 273: 18-34.
    • (2003) J Hydrol , vol.273 , pp. 18-34
    • Zhang, B.1    Govindaraju, R.S.2
  • 61
    • 38149027113 scopus 로고    scopus 로고
    • The research of monthly discharge predictor-corrector model based on wavelet decomposition
    • Zhou HC, Peng Y, Liang G-H (2008) The research of monthly discharge predictor-corrector model based on wavelet decomposition. Water Resour Manag 22(2): 217-227.
    • (2008) Water Resour Manag , vol.22 , Issue.2 , pp. 217-227
    • Zhou, H.C.1    Peng, Y.2    Liang, G.-H.3


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