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Volumn 51, Issue , 2013, Pages 108-117

Modeling rainfall-runoff process using soft computing techniques

Author keywords

Gene expression programming; Neural networks; Neuro fuzzy system; Rainfall runoff process

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; COEFFICIENT OF DETERMINATION; GENE EXPRESSION PROGRAMMING; GOODNESS OF FIT; INDEPENDENT VARIABLES; MEAN ABSOLUTE ERROR; MULTI-LINEAR REGRESSION; NEUROFUZZY SYSTEM; RAINFALL-RUNOFF PROCESS; ROOT MEAN SQUARE ERRORS; SCATTER INDEX; SMALL CATCHMENT; SOFTCOMPUTING TECHNIQUES;

EID: 84870159777     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2012.07.001     Document Type: Article
Times cited : (206)

References (58)
  • 1
    • 43149114256 scopus 로고    scopus 로고
    • An application of artificial intelligence for rainfall runoff modeling
    • Aytek A., Alp M. An application of artificial intelligence for rainfall runoff modeling. Journal of Earth Systems Science 2008, 117(2):145-155.
    • (2008) Journal of Earth Systems Science , vol.117 , Issue.2 , pp. 145-155
    • Aytek, A.1    Alp, M.2
  • 2
    • 39849091610 scopus 로고    scopus 로고
    • A genetic programming approach to suspended sediment modeling
    • Aytek A., Kisi O. A genetic programming approach to suspended sediment modeling. Journal of Hydrology 2008, 351:288-298.
    • (2008) Journal of Hydrology , vol.351 , pp. 288-298
    • Aytek, A.1    Kisi, O.2
  • 3
    • 84855985774 scopus 로고    scopus 로고
    • ANFIS-based approach for predicting sediment transport in clean sewer
    • Azamathulla H, Md.Ab, Ghani A., Seow Y.F. ANFIS-based approach for predicting sediment transport in clean sewer. Applied soft computing 2012, 12:1227-1230.
    • (2012) Applied soft computing , vol.12 , pp. 1227-1230
    • Azamathulla, H.1    Md, A.2    Ghani, A.3    Seow, Y.F.4
  • 4
    • 0036997582 scopus 로고    scopus 로고
    • Rainfall runoff modeling based on genetic programming
    • Babovic V., Keijzer M. Rainfall runoff modeling based on genetic programming. Nordic hydrology 2002, 33:331-343.
    • (2002) Nordic hydrology , vol.33 , pp. 331-343
    • Babovic, V.1    Keijzer, M.2
  • 6
    • 28444489651 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference system for prediction of water level in reservoir
    • Chang F.J., Chang Y.T. Adaptive neuro-fuzzy inference system for prediction of water level in reservoir. Advances in Water Resources 2006, 29:1-10.
    • (2006) Advances in Water Resources , vol.29 , pp. 1-10
    • Chang, F.J.1    Chang, Y.T.2
  • 7
    • 0038240755 scopus 로고    scopus 로고
    • Estimation, forecasting and extrapolation of flow data by artificial neural networks
    • Cigizoglu HK. Estimation, forecasting and extrapolation of flow data by artificial neural networks. Hydrological Sciences Journal 2003, 48(3):349-361.
    • (2003) Hydrological Sciences Journal , vol.48 , Issue.3 , pp. 349-361
    • Cigizoglu, H.K.1
  • 8
    • 0032005702 scopus 로고    scopus 로고
    • An artificial neural network approach to rainfall-runoff modeling
    • Dawson C.W., Wilby R. An artificial neural network approach to rainfall-runoff modeling. Hydrological Sciences Journal 1998, 43:47-66.
    • (1998) Hydrological Sciences Journal , vol.43 , pp. 47-66
    • Dawson, C.W.1    Wilby, R.2
  • 9
    • 0007545218 scopus 로고    scopus 로고
    • Application of Neural Networks and Genetic Programming to Rainfall Runoff Modeling
    • D2K technical report 0699-1-1, Danish Hydraulic Institute, Denmark.
    • Drecourt, J.P., 1999. Application of Neural Networks and Genetic Programming to Rainfall Runoff Modeling. D2K technical report 0699-1-1, Danish Hydraulic Institute, Denmark.
    • (1999)
    • Drecourt, J.P.1
  • 12
    • 0347499408 scopus 로고    scopus 로고
    • Gene expression programming: a new adaptive algorithm for solving problems
    • Ferreira C. Gene expression programming: a new adaptive algorithm for solving problems. Complex Systems 2001, 13(2):87-129.
    • (2001) Complex Systems , vol.13 , Issue.2 , pp. 87-129
    • Ferreira, C.1
  • 17
    • 41749119185 scopus 로고    scopus 로고
    • Genetic programming approach for prediction of local scour downstream hydraulic structures
    • Guven A., Gunal M. Genetic programming approach for prediction of local scour downstream hydraulic structures. Journal of Irrigation and Drainage Engineering 2008, 134(2):241-249.
    • (2008) Journal of Irrigation and Drainage Engineering , vol.134 , Issue.2 , pp. 241-249
    • Guven, A.1    Gunal, M.2
  • 19
    • 0029413797 scopus 로고
    • Artificial neural network modeling of the rainfall-runoff processes
    • Hsu K., Gupta H.V., Sorooshian S. Artificial neural network modeling of the rainfall-runoff processes. Water Resources Research 1995, 31:2517-2530.
    • (1995) Water Resources Research , vol.31 , pp. 2517-2530
    • Hsu, K.1    Gupta, H.V.2    Sorooshian, S.3
  • 20
    • 0027601884 scopus 로고
    • ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems
    • Jang J.S.R. ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems. Man and Cybernetics 1993, 23(3):665-685.
    • (1993) Man and Cybernetics , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.R.1
  • 22
    • 84871962183 scopus 로고    scopus 로고
    • Bilecik-Pazaryeri Kurukavak deresi havzasi yaǧiş, akim karakteristikleri ve sediment verimi, Ara Rapor, Toprak ve Su Kaynaklari Araştirma Enstitüsü, Eskişehir, Yayin No:143
    • Karaş, E., 2006. Bilecik-Pazaryeri Kurukavak deresi havzasi yaǧiş, akim karakteristikleri ve sediment verimi, Ara Rapor, Toprak ve Su Kaynaklari Araştirma Enstitüsü, Eskişehir, Yayin No:143.
    • (2006)
    • Karaş, E.1
  • 23
    • 79951840510 scopus 로고    scopus 로고
    • Nonlinear hydrologic modeling using the stochastic and neural networks approach
    • Kim S. Nonlinear hydrologic modeling using the stochastic and neural networks approach. Disaster Advances 2011, 4(1):53-63.
    • (2011) Disaster Advances , vol.4 , Issue.1 , pp. 53-63
    • Kim, S.1
  • 24
    • 23044459648 scopus 로고    scopus 로고
    • Suspended sediment estimation using neuro-fuzzy and neural network approaches
    • Kisi O. Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrological Sciences Journal 2005, 50(4):683-696.
    • (2005) Hydrological Sciences Journal , vol.50 , Issue.4 , pp. 683-696
    • Kisi, O.1
  • 25
    • 33748933705 scopus 로고    scopus 로고
    • Daily pan evaporation modeling using a neuro-fuzzy computing technique
    • Kisi O. Daily pan evaporation modeling using a neuro-fuzzy computing technique. Journal of Hydrology 2006, 329:636-646.
    • (2006) Journal of Hydrology , vol.329 , pp. 636-646
    • Kisi, O.1
  • 26
    • 34548146808 scopus 로고    scopus 로고
    • Streamflow forecasting using different artificial neural network algorithms
    • Kisi O. Streamflow forecasting using different artificial neural network algorithms. Journal of Hydrologic Engineering 2007, 12(5):532-539.
    • (2007) Journal of Hydrologic Engineering , vol.12 , Issue.5 , pp. 532-539
    • Kisi, O.1
  • 27
    • 41949142664 scopus 로고    scopus 로고
    • River flow forecasting and estimation using different artificial neural network techniques
    • Kisi O. River flow forecasting and estimation using different artificial neural network techniques. Hydrology Research 2008, 39(1):27-40.
    • (2008) Hydrology Research , vol.39 , Issue.1 , pp. 27-40
    • Kisi, O.1
  • 28
    • 68049112473 scopus 로고    scopus 로고
    • Neural networks and wavelet conjunction model for intermittent stream flow forecasting
    • Kisi O. Neural networks and wavelet conjunction model for intermittent stream flow forecasting. Journal of Hydrologic Engineering 2009, 14(8):773-782.
    • (2009) Journal of Hydrologic Engineering , vol.14 , Issue.8 , pp. 773-782
    • Kisi, O.1
  • 29
    • 80053449485 scopus 로고    scopus 로고
    • Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models
    • Kisi O., Shiri J. Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models. Water Resources Management 2011, 25(13):3135-3152.
    • (2011) Water Resources Management , vol.25 , Issue.13 , pp. 3135-3152
    • Kisi, O.1    Shiri, J.2
  • 31
    • 84860608391 scopus 로고    scopus 로고
    • Wavelet and neuro-fuzzy conjunction model for predicting water table depth fluctuations
    • Kisi O., Shiri J. Wavelet and neuro-fuzzy conjunction model for predicting water table depth fluctuations. Hydrology Research 2012, 43(3):286-300.
    • (2012) Hydrology Research , vol.43 , Issue.3 , pp. 286-300
    • Kisi, O.1    Shiri, J.2
  • 32
    • 84859640789 scopus 로고    scopus 로고
    • River suspended sediment estimation by climatic variables implication: comparative study among soft computing techniques
    • Kisi O., Shiri J. River suspended sediment estimation by climatic variables implication: comparative study among soft computing techniques. Computers & Geosciences 2012, 43:73-82.
    • (2012) Computers & Geosciences , vol.43 , pp. 73-82
    • Kisi, O.1    Shiri, J.2
  • 33
    • 84857912130 scopus 로고    scopus 로고
    • Forecasting daily lake levels using artificial intelligence approaches
    • Kisi O., Shiri J., Nikoofar B. Forecasting daily lake levels using artificial intelligence approaches. Computers & Geosciences 2012, 41:169-180.
    • (2012) Computers & Geosciences , vol.41 , pp. 169-180
    • Kisi, O.1    Shiri, J.2    Nikoofar, B.3
  • 34
  • 36
    • 0032920124 scopus 로고    scopus 로고
    • Evaluating the use of goodness-of-fit measures in hydrologic and hydroclimatic validation
    • Legates D.R., McCabe G.J. Evaluating the use of goodness-of-fit measures in hydrologic and hydroclimatic validation. Water Resources Research 1999, 35(1):233-241.
    • (1999) Water Resources Research , vol.35 , Issue.1 , pp. 233-241
    • Legates, D.R.1    McCabe, G.J.2
  • 38
  • 40
    • 0029748915 scopus 로고    scopus 로고
    • A neural network model of rainfall-runoff using radial basis functions
    • Mason J.C., Price A.K., Temme A. A neural network model of rainfall-runoff using radial basis functions. Journal of Hydraulic Research 1996, 34:537-548.
    • (1996) Journal of Hydraulic Research , vol.34 , pp. 537-548
    • Mason, J.C.1    Price, A.K.2    Temme, A.3
  • 41
    • 0030159380 scopus 로고    scopus 로고
    • Artificial neural networks as rainfall-runoff models
    • Minns A.W., Hall M.J. Artificial neural networks as rainfall-runoff models. Hydrological Sciences Journal 1996, 41(3):399-418.
    • (1996) Hydrological Sciences Journal , vol.41 , Issue.3 , pp. 399-418
    • Minns, A.W.1    Hall, M.J.2
  • 42
    • 57949098440 scopus 로고    scopus 로고
    • Determining turbulent flow friction coefficient using adaptive neuro-fuzzy computing technique
    • Ozger M., Yildirim G. Determining turbulent flow friction coefficient using adaptive neuro-fuzzy computing technique. Advances in Engineering Software 2009, 40:281-287.
    • (2009) Advances in Engineering Software , vol.40 , pp. 281-287
    • Ozger, M.1    Yildirim, G.2
  • 43
    • 84871944378 scopus 로고    scopus 로고
    • Covariant Parsimony Pressure for Genetic Programming
    • Technical Report CES-480, ISSN:1744-8050.
    • Ploi, R., McPhee, N.F., 2008. Covariant Parsimony Pressure for Genetic Programming. Technical Report CES-480, ISSN:1744-8050.
    • (2008)
    • Ploi, R.1    McPhee, N.F.2
  • 45
    • 78149414268 scopus 로고    scopus 로고
    • Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model
    • Shiri J., Kisi O. Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model. Journal of Hydrology 2010, 394(3-4):486-493.
    • (2010) Journal of Hydrology , vol.394 , Issue.3-4 , pp. 486-493
    • Shiri, J.1    Kisi, O.2
  • 46
    • 80052542665 scopus 로고    scopus 로고
    • Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations
    • Shiri J., Kisi O. Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations. Computers & Geosciences 2011, 37(10):1692-1701.
    • (2011) Computers & Geosciences , vol.37 , Issue.10 , pp. 1692-1701
    • Shiri, J.1    Kisi, O.2
  • 47
    • 79960111650 scopus 로고    scopus 로고
    • Application of artificial intelligence to estimate daily pan evaporation using available and estimated climatic data in the Khozestan Province (Southwestern Iran)
    • Shiri J., Kisi O. Application of artificial intelligence to estimate daily pan evaporation using available and estimated climatic data in the Khozestan Province (Southwestern Iran). Journal of Irrigation and Drainage Engineering 2011, 37(7):412-425.
    • (2011) Journal of Irrigation and Drainage Engineering , vol.37 , Issue.7 , pp. 412-425
    • Shiri, J.1    Kisi, O.2
  • 48
    • 82455186243 scopus 로고    scopus 로고
    • Estimating daily pan evaporation from climatic data of the state of Illinois, USA using adaptive neuro-fuzzy inference system and artificial neural network
    • Shiri J., Dierickx W., Pour-Ali Baba A., Nemati S., Ghorbani M.A. Estimating daily pan evaporation from climatic data of the state of Illinois, USA using adaptive neuro-fuzzy inference system and artificial neural network. Hydrology Research 2011, 42(6):491-502.
    • (2011) Hydrology Research , vol.42 , Issue.6 , pp. 491-502
    • Shiri, J.1    Dierickx, W.2    Pour-Ali Baba, A.3    Nemati, S.4    Ghorbani, M.A.5
  • 50
    • 84855193767 scopus 로고    scopus 로고
    • Daily refernec evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)
    • Shiri J., Kisi O., Landeras G., Lopez J.J., Nazemi A.H., Stuyt L.C.P.M. Daily refernec evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain). Journal of Hydrology 2012, 414-415:302-316.
    • (2012) Journal of Hydrology , vol.414-415 , pp. 302-316
    • Shiri, J.1    Kisi, O.2    Landeras, G.3    Lopez, J.J.4    Nazemi, A.H.5    Stuyt, L.C.P.M.6
  • 52
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its application to modeling and control
    • Takagi T., Sugeno M. Fuzzy identification of systems and its application to modeling and control. IEEE Transactions on System, Man and Cybernetics 1985, 15(1):116-132.
    • (1985) IEEE Transactions on System, Man and Cybernetics , vol.15 , Issue.1 , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 53
    • 33751081243 scopus 로고    scopus 로고
    • ANN and fuzzy logic models for simulating event-based rainfall-runoff
    • Tayfur G., Singh V.P. ANN and fuzzy logic models for simulating event-based rainfall-runoff. Journal of Hydrologic Engineering 2006, 132:1321-1330.
    • (2006) Journal of Hydrologic Engineering , vol.132 , pp. 1321-1330
    • Tayfur, G.1    Singh, V.P.2
  • 54
    • 34447334519 scopus 로고    scopus 로고
    • Predicting and forecasting flow discharge at sites receiving significant lateral inflow
    • Tayfur G., Moramorco T., Singh V.P. Predicting and forecasting flow discharge at sites receiving significant lateral inflow. Hydrological Processes 2007, 21:1848-1859.
    • (2007) Hydrological Processes , vol.21 , pp. 1848-1859
    • Tayfur, G.1    Moramorco, T.2    Singh, V.P.3
  • 55
    • 0033167344 scopus 로고    scopus 로고
    • Rainfall-runoff modeling using artificial neural networks
    • Tokar A.S., Johnson P.A. Rainfall-runoff modeling using artificial neural networks. Journal of Hydrologic Engineering 1999, 4:232-239.
    • (1999) Journal of Hydrologic Engineering , vol.4 , pp. 232-239
    • Tokar, A.S.1    Johnson, P.A.2
  • 56
    • 18944367990 scopus 로고    scopus 로고
    • Researh note: "determination of soil hydraulic properties using pedotransfer functions in a semi-arid basin, Turkey"
    • Tombul M., Akyürek Z., Şorman A.Ü. Researh note: "determination of soil hydraulic properties using pedotransfer functions in a semi-arid basin, Turkey". Hydrologic and Earth Systems Science 2004, 8:1200-1209.
    • (2004) Hydrologic and Earth Systems Science , vol.8 , pp. 1200-1209
    • Tombul, M.1    Akyürek, Z.2    Şorman, A.Ü.3
  • 57
    • 84871970808 scopus 로고    scopus 로고
    • Temsili Hidrolojik Havzalarda Benzeşim Kriterlerinin Araştirilmasi ve Modellenmesi
    • Anadolu Üniversitesi Bilimsel Araştirma Projesi,Proje No: 00261
    • Tombul, M., Akyürek, Z., Şorman, A.Ü., Ayday, E., Öǧretir, K., 2004b. Temsili Hidrolojik Havzalarda Benzeşim Kriterlerinin Araştirilmasi ve Modellenmesi. Anadolu Üniversitesi Bilimsel Araştirma Projesi,Proje No: 00261.
    • (2004)
    • Tombul, M.1    Akyürek, Z.2    Şorman, A.Ü.3    Ayday, E.4    Öǧretir, K.5
  • 58
    • 58849094959 scopus 로고    scopus 로고
    • Modeling level change in lakes using neuro-fuzzy and artificial neural networks
    • Yarar A., Onucyildiz M., Copty N.K. Modeling level change in lakes using neuro-fuzzy and artificial neural networks. Journal of Hydrology 2009, 365:329-334.
    • (2009) Journal of Hydrology , vol.365 , pp. 329-334
    • Yarar, A.1    Onucyildiz, M.2    Copty, N.K.3


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