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Volumn 361, Issue 1-2, 2008, Pages 118-130

A new indirect multi-step-ahead prediction model for a long-term hydrologic prediction

Author keywords

Adaptive time delay neural network; Indirect multi step ahead prediction; Spline interpolation; Time delay neural network

Indexed keywords

BENCHMARKING; INTERPOLATION; MATHEMATICAL MODELS; NEURAL NETWORKS; OFFSHORE OIL WELL PRODUCTION; PLANNING; SOLAR ENERGY; SPLINES; TIME DELAY; TIME SERIES ANALYSIS; WATER MANAGEMENT;

EID: 52949137358     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2008.07.040     Document Type: Article
Times cited : (45)

References (51)
  • 1
    • 0036034561 scopus 로고    scopus 로고
    • Ahmad, Z., Zhang J., 2002. Improving long range prediction for nonlinear process modeling through combining multiple neural network. In: Proceeding of the 2002 IEEE International Conference on Control Applications, pp. 966-971.
    • Ahmad, Z., Zhang J., 2002. Improving long range prediction for nonlinear process modeling through combining multiple neural network. In: Proceeding of the 2002 IEEE International Conference on Control Applications, pp. 966-971.
  • 2
    • 0037199734 scopus 로고    scopus 로고
    • The use of the aridity index to assess climate change effect on annual runoff
    • Arora V.K. The use of the aridity index to assess climate change effect on annual runoff. Journal of Hydrology 265 (2002) 164-177
    • (2002) Journal of Hydrology , vol.265 , pp. 164-177
    • Arora, V.K.1
  • 3
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology-II: hydrological applications
    • ASCE Task Committee. Artificial neural networks in hydrology-II: hydrological applications. Journal of Hydrologic Engineering, ASCE 5 2 (2000) 124-137
    • (2000) Journal of Hydrologic Engineering, ASCE , vol.5 , Issue.2 , pp. 124-137
    • ASCE Task Committee1
  • 4
  • 5
    • 84964495026 scopus 로고    scopus 로고
    • Boné, R., Crucianu, M., 2002a. An evaluation of constructive algorithms for recurrent networks on multi-step-ahead prediction. In: ICONIP'02 Proceedings of the 9th International Conference on Neural Information Processing, vol. 2, pp. 547-551.
    • Boné, R., Crucianu, M., 2002a. An evaluation of constructive algorithms for recurrent networks on multi-step-ahead prediction. In: ICONIP'02 Proceedings of the 9th International Conference on Neural Information Processing, vol. 2, pp. 547-551.
  • 7
    • 33748929857 scopus 로고    scopus 로고
    • Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River
    • Chau K.W. Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River. Journal of Hydrology 329 3-4 (2006) 363-367
    • (2006) Journal of Hydrology , vol.329 , Issue.3-4 , pp. 363-367
    • Chau, K.W.1
  • 8
    • 27544472438 scopus 로고    scopus 로고
    • Comparison of several flood forecasting models in Yangtze River
    • Chau K.W., Wu C.L., and Li Y.S. Comparison of several flood forecasting models in Yangtze River. Journal of Hydrologic Engineering, ASCE 10 6 (2005) 485-491
    • (2005) Journal of Hydrologic Engineering, ASCE , vol.10 , Issue.6 , pp. 485-491
    • Chau, K.W.1    Wu, C.L.2    Li, Y.S.3
  • 9
    • 10244232843 scopus 로고    scopus 로고
    • a web-based flood forecasting system for reservoirs with J2EE
    • Cheng C.T., Chau K.W., Li X.Y., and Li G. a web-based flood forecasting system for reservoirs with J2EE. Hydrological Sciences Journal 49 6 (2004) 973-986
    • (2004) Hydrological Sciences Journal , vol.49 , Issue.6 , pp. 973-986
    • Cheng, C.T.1    Chau, K.W.2    Li, X.Y.3    Li, G.4
  • 10
    • 28744454934 scopus 로고    scopus 로고
    • Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure
    • Cheng C.T., Zhao M.Y., Chau K.W., and Wu X.Y. Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure. Journal of Hydrology 316 1-4 (2006) 129-140
    • (2006) Journal of Hydrology , vol.316 , Issue.1-4 , pp. 129-140
    • Cheng, C.T.1    Zhao, M.Y.2    Chau, K.W.3    Wu, X.Y.4
  • 12
    • 0032207527 scopus 로고    scopus 로고
    • Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks and probabilistic neural networks
    • Emad E.W., Prokhorov D.V., and Wunsch D.C. Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks and probabilistic neural networks. IEEE Transactions on Neural Networks 9 6 (1998) 1456-1469
    • (1998) IEEE Transactions on Neural Networks , vol.9 , Issue.6 , pp. 1456-1469
    • Emad, E.W.1    Prokhorov, D.V.2    Wunsch, D.C.3
  • 14
  • 15
    • 0026838551 scopus 로고
    • Multiplicative, season ARIMA models for Lake Erie and Lake Ontario water levels
    • Irvine K.N., and Eberhardt A.J. Multiplicative, season ARIMA models for Lake Erie and Lake Ontario water levels. Water Resources Bulletin 28 2 (1992) 385-396
    • (1992) Water Resources Bulletin , vol.28 , Issue.2 , pp. 385-396
    • Irvine, K.N.1    Eberhardt, A.J.2
  • 16
    • 0036475142 scopus 로고    scopus 로고
    • Characterization and prediction of runoff dynamics: a nonlinear dynamical view
    • Islam M.N., and Sivakumar B. Characterization and prediction of runoff dynamics: a nonlinear dynamical view. Advances in Water Resources 25 2 (2002) 179-190
    • (2002) Advances in Water Resources , vol.25 , Issue.2 , pp. 179-190
    • Islam, M.N.1    Sivakumar, B.2
  • 17
    • 0042878315 scopus 로고    scopus 로고
    • Analysis of long-term variations in the Volga annual runoff
    • Ismaiylov G.K., and Fedorov V.M. Analysis of long-term variations in the Volga annual runoff. Water Resources 28 5 (2001) 469-477
    • (2001) Water Resources , vol.28 , Issue.5 , pp. 469-477
    • Ismaiylov, G.K.1    Fedorov, V.M.2
  • 18
    • 11944266539 scopus 로고
    • Information theory and statistical mechanics
    • Jaynes E.T. Information theory and statistical mechanics. Physical Review 106 (1957) 620-630
    • (1957) Physical Review , vol.106 , pp. 620-630
    • Jaynes, E.T.1
  • 20
    • 33646572227 scopus 로고    scopus 로고
    • Chaotic time series prediction with a global model: Artificial neural network
    • Karunasinghe D.S.K., and Liong S.-Y. Chaotic time series prediction with a global model: Artificial neural network. Journal of Hydrology 323 1-4 (2006) 92-105
    • (2006) Journal of Hydrology , vol.323 , Issue.1-4 , pp. 92-105
    • Karunasinghe, D.S.K.1    Liong, S.-Y.2
  • 22
    • 1642497522 scopus 로고    scopus 로고
    • River flow modeling using artificial neural networks
    • Kisi O. River flow modeling using artificial neural networks. Journal of Hydrologic Engineering 9 1 (2004) 60-63
    • (2004) Journal of Hydrologic Engineering , vol.9 , Issue.1 , pp. 60-63
    • Kisi, O.1
  • 23
    • 0028792642 scopus 로고
    • Maximum entropy spectral analysis of the Duero Basin International
    • Letie S.M. Maximum entropy spectral analysis of the Duero Basin International. Journal of Climatology 15 4 (1995) 463-472
    • (1995) Journal of Climatology , vol.15 , Issue.4 , pp. 463-472
    • Letie, S.M.1
  • 24
    • 0029079025 scopus 로고
    • Trajectory Production with the adaptive time-delay neural network
    • Lin D.T., Dayhoff J.E., and Ligomenides P.A. Trajectory Production with the adaptive time-delay neural network. Neural Networks 8 3 (1995) 447-461
    • (1995) Neural Networks , vol.8 , Issue.3 , pp. 447-461
    • Lin, D.T.1    Dayhoff, J.E.2    Ligomenides, P.A.3
  • 25
    • 33746830757 scopus 로고    scopus 로고
    • Using support vector machines for long-term discharge prediction
    • Lin J.Y., Cheng C.T., and Chau K.W. Using support vector machines for long-term discharge prediction. Hydrological Sciences Journal 51 4 (2006) 599-612
    • (2006) Hydrological Sciences Journal , vol.51 , Issue.4 , pp. 599-612
    • Lin, J.Y.1    Cheng, C.T.2    Chau, K.W.3
  • 26
    • 52949084009 scopus 로고    scopus 로고
    • Efficient implementation of inverse approach for forecasting hydrological time series using micro GA
    • Liong S.Y., Phoon K.K., and Pasha M.F.K. Efficient implementation of inverse approach for forecasting hydrological time series using micro GA. Journal Of Hydroinformatics 7 3 (2005) 151-163
    • (2005) Journal Of Hydroinformatics , vol.7 , Issue.3 , pp. 151-163
    • Liong, S.Y.1    Phoon, K.K.2    Pasha, M.F.K.3
  • 27
    • 0034737033 scopus 로고    scopus 로고
    • A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting
    • Luk K.C., Ball J.E., and Sharma A. A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting. Journal of Hydrology 227 1 (2000) 56-65
    • (2000) Journal of Hydrology , vol.227 , Issue.1 , pp. 56-65
    • Luk, K.C.1    Ball, J.E.2    Sharma, A.3
  • 28
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications
    • Maier H., and Dandy G.C. Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications. Environmental Modelling Software 15 (1999) 101-124
    • (1999) Environmental Modelling Software , vol.15 , pp. 101-124
    • Maier, H.1    Dandy, G.C.2
  • 30
    • 0028667757 scopus 로고
    • Climate, soil water storage, and the average annual water balance
    • Milly P.C.D. Climate, soil water storage, and the average annual water balance. Water Resources Research 30 (1994) 2143-2156
    • (1994) Water Resources Research , vol.30 , pp. 2143-2156
    • Milly, P.C.D.1
  • 32
    • 0032093014 scopus 로고    scopus 로고
    • Real-time control of systems with unknown and varying time-delays using neural networks
    • Ng G.W., and Cook P.A. Real-time control of systems with unknown and varying time-delays using neural networks. Engineering Applications of Artificial Intelligence 11 3 (1998) 401-409
    • (1998) Engineering Applications of Artificial Intelligence , vol.11 , Issue.3 , pp. 401-409
    • Ng, G.W.1    Cook, P.A.2
  • 33
    • 33845600932 scopus 로고    scopus 로고
    • Cluster-based hydrologic prediction using genetic algorithm-trained neural networks
    • Parasuraman K., and Elshorbagy A. Cluster-based hydrologic prediction using genetic algorithm-trained neural networks. Journal of Hydrologic Engineering 12 1 (2007) 52-62
    • (2007) Journal of Hydrologic Engineering , vol.12 , Issue.1 , pp. 52-62
    • Parasuraman, K.1    Elshorbagy, A.2
  • 34
    • 0034269158 scopus 로고    scopus 로고
    • Multi-step-ahead prediction using dynamic recurrent neural networks
    • Parlos A.G., Rais O.T., and Atiya A.F. Multi-step-ahead prediction using dynamic recurrent neural networks. Neural Networks 13 5 (2000) 765-786
    • (2000) Neural Networks , vol.13 , Issue.5 , pp. 765-786
    • Parlos, A.G.1    Rais, O.T.2    Atiya, A.F.3
  • 37
    • 0141988812 scopus 로고    scopus 로고
    • Time-delay neural network for the prediction of carbonation tower's temperature
    • Shi D., Zhang H.J., and Yang L.M. Time-delay neural network for the prediction of carbonation tower's temperature. IEEE Transactions on Instrumentation and Measurement 52 4 (2003) 1125-1128
    • (2003) IEEE Transactions on Instrumentation and Measurement , vol.52 , Issue.4 , pp. 1125-1128
    • Shi, D.1    Zhang, H.J.2    Yang, L.M.3
  • 38
    • 0031141905 scopus 로고    scopus 로고
    • The use of entropy in hydrology and water resource
    • Singh V.P. The use of entropy in hydrology and water resource. Hydrological Processes 11 (1997) 587-626
    • (1997) Hydrological Processes , vol.11 , pp. 587-626
    • Singh, V.P.1
  • 40
    • 0025898196 scopus 로고
    • Long-range streamflow forecasting using non-parametric regression
    • Smith J.A. Long-range streamflow forecasting using non-parametric regression. Water Resources Bulletin 27 1 (1991) 39-46
    • (1991) Water Resources Bulletin , vol.27 , Issue.1 , pp. 39-46
    • Smith, J.A.1
  • 41
    • 0033078453 scopus 로고    scopus 로고
    • Neural-network-based d-step-ahead predictors for nonlinear systems with time delay
    • Tan Y., and Cauwenberghe A.V. Neural-network-based d-step-ahead predictors for nonlinear systems with time delay. Engineering Applications of Artificial Intelligence 12 1 (1999) 21-35
    • (1999) Engineering Applications of Artificial Intelligence , vol.12 , Issue.1 , pp. 21-35
    • Tan, Y.1    Cauwenberghe, A.V.2
  • 42
    • 3343015044 scopus 로고    scopus 로고
    • Tarczynski, A., Kozinski, W., Cain, G.D., 1994. Sampling rate conversion using fractional-sample delay, ICASSP, pp. 285-288.
    • Tarczynski, A., Kozinski, W., Cain, G.D., 1994. Sampling rate conversion using fractional-sample delay, ICASSP, pp. 285-288.
  • 43
    • 0002999362 scopus 로고    scopus 로고
    • Splines: a perfect fit for signal and image processing
    • Unser M. Splines: a perfect fit for signal and image processing. IEEE Signal Processing Magazine 16 6 (1999) 22-38
    • (1999) IEEE Signal Processing Magazine , vol.16 , Issue.6 , pp. 22-38
    • Unser, M.1
  • 45
    • 34447630402 scopus 로고    scopus 로고
    • Research on cryptic period of hydrologic time series based on MEM1 spectral analysis
    • Wang D., and Zhu Y.S. Research on cryptic period of hydrologic time series based on MEM1 spectral analysis. Chinese Journal of Hydrology 22 2 (2002) 19-23
    • (2002) Chinese Journal of Hydrology , vol.22 , Issue.2 , pp. 19-23
    • Wang, D.1    Zhu, Y.S.2
  • 47
    • 33845421111 scopus 로고    scopus 로고
    • A flood forecasting neural network model with genetic algorithm
    • Wu C.L., and Chau K.W. A flood forecasting neural network model with genetic algorithm. International Journal of Environment and Pollution 28 3-4 (2006) 261-273
    • (2006) International Journal of Environment and Pollution , vol.28 , Issue.3-4 , pp. 261-273
    • Wu, C.L.1    Chau, K.W.2
  • 48
    • 0030746409 scopus 로고    scopus 로고
    • Time delay neural networks for the classification of flow regimes
    • Yamashita Y. Time delay neural networks for the classification of flow regimes. Computers and Chemical Engineering 21 (1997) 6367-6371
    • (1997) Computers and Chemical Engineering , vol.21 , pp. 6367-6371
    • Yamashita, Y.1
  • 49
    • 0036707312 scopus 로고    scopus 로고
    • Adaptive time delay neural network structures for nonlinear system identification
    • Yazdizadeh A., and Khorasani K. Adaptive time delay neural network structures for nonlinear system identification. Neurocomputing 47 (2002) 207-240
    • (2002) Neurocomputing , vol.47 , pp. 207-240
    • Yazdizadeh, A.1    Khorasani, K.2
  • 51
    • 0037243071 scopus 로고    scopus 로고
    • Time series forecasting using a hybrid ARIMA and neural network model
    • Zhang P.G. Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50 (2003) 159-175
    • (2003) Neurocomputing , vol.50 , pp. 159-175
    • Zhang, P.G.1


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