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Special Topics & Reviews in Porous Media: An International Journal
ESCI SJR: 0.277 SNIP: 0.52 CiteScore™: 1.3

ISSN 印刷: 2151-4798
ISSN オンライン: 2151-562X

Special Topics & Reviews in Porous Media: An International Journal

DOI: 10.1615/SpecialTopicsRevPorousMedia.2017019729
pages 145-157

ARTIFICIAL NEURAL NETWORK FOR BED LOAD TRANSPORT RATE IN NESTOS RIVER, GREECE

Thomas Papalaskaris
Division of Hydraulic Engineering, Department of Civil Engineering, Democritus University of Thrace, Xanthi, 67132, Greece
P. Dimitriadou
Division of Hydraulic Engineering, Department of Civil Engineering, Democritus University of Thrace, Xanthi, 67132, Greece

要約

Within the framework of diploma theses elaborated at the Division of Hydraulic Engineering, Department of Civil Engineering, Democritus University of Thrace, measurements of stream discharge and bed load transport rate (experiments in enviromental flow) were carried out at the outlet of the mountainous part of the Nestos River basin (northeastern Greece). In concrete terms, 68 measurements of stream discharge and bed load transport rate were carried out at a location near the basin outlet. Apart from the measurements, the bed load transport rate was computed using the Meyer-Peter-Muller formula, after calibrating the formula in terms of the roughness coefficient. Comparison of the results obtained from the computations and measurements of the bed load transport rate, based on well-known statistical criteria, were fairly satisfactory. Finally, we build an artificial neural network, a data-driven technique, and investigate how well this simulates the site-measured bed load transport rate values.


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