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Original Articles

Estimation of parameters of the transient storage model by means of multi-layer perceptron neural networks / Estimation des paramètres du modèle de transport TSM au moyen de réseaux de neurones perceptrons multi-couches

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Pages 165-178 | Received 05 Jun 2007, Accepted 04 Oct 2007, Published online: 18 Jan 2010

REFERENCES

  • Anctil , F. , Michel , C. , Perrin , C. and Andreassian , V. 2004 . A soil moisture index as an auxiliary ANN input for stream flow forecasting. . J. Hydrol. , 286 : 155 – 167 .
  • Bencala , K. E. and Walters , R. A. 1983 . Simulation of solute transport in a mountain pool-and-riffle stream: a transient storage model. . Water Resour. Res. , 19 ( 3 ) : 718 – 724 .
  • Brath , A. , Montanari , A. and Toth , E. 2002 . Neural networks and non-parametric methods for improving real-time flood forecasting through conceptual hydrological models. . Hydrol. Earth System Sci. , 6 ( 4 ) : 627 – 640 .
  • Caplow , T. , Schlosser , P. and Ho , D. 2004 . Tracer study of mixing and transport in the upper Hudson River with multiple dams . J. Environ. Engng , 130 : 1498 – 1506 .
  • Cheong , T. S. and Seo , I. W. 2003 . Parameter estimation of the transient storage model by a routing method for river mixing processes. . Water Resour. Res. , 39 ( 4 ) : 1074 – 1084 .
  • Cheong , T. S. , Younis , B. A. and Seo , I. W. 2007 . Estimation of key parameters in model for solute transport in rivers and streams. . Water Resour. Manage. , 21 ( 7 ) : 1165 – 1186 .
  • Clerc , M. 2006 . Particle Swarm Optimization. London , , UK : ISTE Ltd .
  • Czernuszenko , W. and Rowiński , P. M. 1997 . Properties of the dead-zone model of longitudinal dispersion in rivers. . J. Hydraul. Res. , 35 ( 4 ) : 491 – 504 .
  • Czernuszenko , W. , Rowiński , P. M. and Sukhodolov , A. 1998 . Experimental and numerical validation of the dead-zone model for longitudinal dispersion in rivers. . J. Hydraul. Res. , 36 ( 2 ) : 269 – 280 .
  • De Smedt , F. , Brevis , W. and Debels , P. 2005 . Analytical solution for solute transport resulting from instantaneous injection in streams with transient storage. . J. Hydrol. , 315 : 25 – 39 .
  • Deng , Z. Q. , Singh , V. P. and Bengtsson , L. 2001 . Longitudinal dispersion coefficient in straight rivers. . J. Hydraul. Engng ASCE , 127 ( 11 ) : 919 – 927 .
  • Du , J. X. , Huang , D. S. , Wang , X. F. and Gu , X. 2007 . Shape recognition based on neural networks trained by differential evolution algorithm. . Neurocomputing , 70 (4/6) : 896 – 903 .
  • Fisher , H. B. 1968 . “ Method for predicting dispersion coefficients in natural streams, with applications to lower reaches of the Green and Duwamish Rivers ” . In US Geol. Survey Prof. Paper 582-A. Washington
  • Gaume , E. and Gosset , R. 2003 . Over-parameterisation, a major obstacle to the use of artificial neural networks in hydrology? . Hydrol. Earth System Sci. , 7 ( 5 ) : 693 – 706 .
  • Godfrey , R. G. and Frederick , B. J. 1970 . Stream dispersion at selected sites . US Geological Survey Professional Paper, 433—K. ,
  • Graf , J. B. 1995 . Measured and predicted velocity and longitudinal dispersion at steady and unsteady flow, Colorado River, Glen Canyon Dam to Lake Mead. . Water Resour. Bull. , 31 ( 2 ) : 265 – 281 .
  • Guymer , I. and Dutton , R. 2005 . “ Application of a transient storage model to meandering channel studies of solute transport and dispersion. ” . In Water Quality Hazards and Dispersion of Pollutants , Edited by: Czernuszenko , W. and Rowiński , P. M. 85 – 107 . New York , , USA : Springer .
  • Hart , D. R. 1995 . Parameter estimation and stochastic interpretation of the transient storage model for solute transport in streams. . Water Resour. Res , 31 ( 2 ) : 323 – 328 .
  • Haykin , S. 1994 . Neural Networks, a Comprehensive Foundation. New York , , USA : Macmillan College Publishing Co. .
  • Ilonen , J. , Kamarainen , J. K. and Lampinen , J. 2003 . Differential Evolution training algorithm for feed-forward neural networks. . Neural Processing Letters , 17 : 93 – 105 .
  • Kashefipour , S. M. and Falconer , R. A. 2002 . Longitudinal dispersion coefficients in natural channels. . Water Research , 36 : 1596 – 1608 .
  • Kashefipour , S. M. , Falconer , R. A. and Lin , B. 2002 . “ Modeling longitudinal dispersion in natural channel flows using ANNs. ” . In River Flow 2002 Edited by: Bousmar , D. , Zech , Y. , Balkema/Swets , A. A. and Lisse , Zeitlinger . 111 – 116 . The Netherlands
  • Kennedy , J. and Eberhart , R. C. 1995 . “ Particle Swarm Optimization. ” . In Proceedings of the International Conference on Evolutionary Computation Perth , , Australia
  • Lees , M. J. , Camacho , L. A. and Chapra , S. C. 2000 . On the relationship of transient storage and aggregated dead zone models of longitudinal solute transport in streams. . Water Resour. Res. , 36 ( 1 ) : 213 – 224 .
  • Lin , W. Q. , Jiang , J. H. , Zhou , Y. P. , Wu , H. L. , Shen , G. L. and Yu , R. Q. 2007 . Support vector machine based training of multilayer feedforward neural networks as optimized by Particle Swarm algorithm: Application in QSAR studies of bioactivity of organic compounds. . J. Comput. Chemistry , 28 ( 2 ) : 519 – 527 .
  • van Mazijk , A. and Veling , E. J. M. 2005 . “ Persistence of skewness of concentration distribution. ” . In Water Quality Hazards and Dispersion of Pollutants , Edited by: Czernuszenko , W. and Rowiński , P. M. 143 – 168 . New York , , USA : Springer .
  • Mishra , S. K. 2006a . “ Global optimization by Particle Swarm method: a FORTRAN program. ” . In Social Science Research Network, Working Papers Series http://ssrn.com/abstract=921504.
  • Mishra , S. K. 2006b . Global optimization by differential evolution and particle swarm methods evaluation on some benchmark functions. . Social Science Research Network, Working Papers Series , http://ssrn.com/abstract=933827.
  • Natarajan , U. , Periasamy , V. M. and Saravanan , R. 2007 . Application of Particle Swarm optimization in artificial neural network for the prediction of tool life. . Int. J. Advanced Manufacturing. Technology , 31 (9/10) : 871 – 876 .
  • Nordin , C. F. and Sabol , G. V. 1974 . Empirical data on longitudinal dispersion. . US Geol. Survey Water Resour. Investigations , : 20 – 74 .
  • Nordin , C. F. and Troutman , B. M. 1980 . Longitudinal dispersion in rivers: the persistence of skewness in observed data. . Water Resour. Res. , 16 ( 1 ) : 123 – 128 .
  • Pedersen , F. B. 1977 . “ Prediction on longitudinal dispersion in natural streams. Hydrodynamis and Hydraulic Engineering Series Paper no. 14 ” . Technical University of Denmark. .
  • Piotrowski , A. , Rowiński , P. M. and Napiórkowski , J. J. 2006a . Flash-flood forecasting by means of neural networks and nearest neighbour approach—a comparative study. . Nonlinear Processes in Geophysics , 13 : 443 – 448 .
  • Piotrowski , A. , Rowiński , P. M. and Napiórkowski , J. J. 2006b . “ Assessment of longitudinal dispersion coefficient by means of different neural networks. ” . In 7th Int. Conf. on Hydroinformatics , Edited by: Gourbesville , P. , Cunge , J. , Guinot , V. and Liong , S. Y. Nice , , France : Research Publishing. HIC 2006 .
  • Press , W. H. , Flannery , B. P. , Teukolsky , S. A. and Vetterling , W. T. 1990 . Numerical Recipes in C. The Art of Scientific Computing. Cambridge , , UK : Cambridge University Press .
  • Price , K. V. , Storn , R. M. and Lampinen , J. A. 2005 . Differential Evolution. A Practical Approach to Global Optimization. Berlin , , Germany : Springer-Verlag .
  • Rowiński , P. M. , Aberle , J. and Mazurczyk , A. 2005a . Shear velocity estimation in hydraulic research. . Acta Geophys. Pol. , 53 ( 4 ) : 567 – 583 .
  • Rowiński , P. M. , Piotrowski , A. and Napiórkowski , J. J. 2005b . Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? . Hydrol. Sci. J. , 50 ( 1 ) : 175 – 187 .
  • Rowiński , P. M. , Guymer , I. , Bielonko , A. , Napiórkowski , J. J. , Pearson , J. and Piotrowski , A. 2007 . “ Large scale tracer study of mixing in a natural lowland river. ” . In Proc. 32nd Congress Venice , , Italy : IAHR .
  • Seo , I. W. and Yu , D. 2000 . Modeling solute transport in pool-and-riffle streams. . Water Engng Res. , 1 (2)
  • Storn , R. and Price , K. V. 1995 . “ Differential Evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces. ” . In Tech. Report TR-95-012 Berkeley, California , , USA : International Computer Sciences Institute .
  • Sukhodolov , A. N. , Nikora , V. I. , Rowiński , P. M. and Czernuszenko , W. 1997 . A case study of longitudinal dispersion in small lowland rivers. . Water Environ. Res. , 69 ( 7 ) : 1246 – 1253 .
  • Tayfur , G. and Singh , V. P. 2005 . Predicting longitudinal dispersion coefficient in natural streams by artificial neural network. . J. Hydraul. Engng ASCE , 131 ( 11 ) : 991 – 1000 .
  • Uijttewaal , W. S. J. , Lehmann , D. and van Mazijk , A. 2001 . Exchange processes between a river and its groyne fields: model experiments. . J. Hydraul. Engng ASCE , 127 ( 11 ) : 928 – 936 .
  • Wallis , S. G. and Manson , J. R. 2004 . Methods for predicting dispersion coefficients in rivers. . Water Manage. , 157 ( WM3 ) : 131 – 141 .
  • Wei , X. Y. and Pan , H. X. 2006 . Neural networks trained with particle swarm optimization for fault diagnosis. . Applications & Algorithms , 13 : 302 – 306 . Dynamics of Continuous Discrete and Impulsive Systems Series B: Part 1 Suppl. S.
  • White , W. R. , Milli , H. and Crabbe , A. D. 1973 . Vol. 2 , Wallingford , , UK : Hydraulic Research Station Report no. IT119 . Sediment transport: an appraisal methods, vol. 2: Performance of theoretical methods when applied to flume and field data.
  • Yu , B. and He , X. 2006 . Training radial basis function networks with differential evolution. . Transactions on Engineering, Computing and Technology , V11 : 157 – 160 .

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