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Titel:

ANN optimized by PSO and Firefly algorithms for predicting scour depths around bridge piers

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Dang, Nguyen Mai; Tran Anh, Duong; Dang, Thanh Duc:
Abstract:
The estimation of scour depths is extremely important in designing the foundation of piers which ensure the integrity of bridges and other hydraulic structures. Complicated hydrodynamic processes around piers are the main challenge to formulate explicitly empirical equations in providing scour depth estimation. Consequently, the proposed empirical formulae only yield good prediction results for specific conditions. In this study, the particle swarm optimization and Firefly algorithms are pro...     »
Stichworte:
Artificial neural network (ANN); Scour; Bridge pier; Particle swarm optimization (PSO); Levenberg–Marquardt algorithm (LM); Firefly algorithm (FA)
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften
Zeitschriftentitel:
Engineering with Computers
Jahr:
2021
Band / Volume:
Vol. 37
Heft / Issue:
1
Seitenangaben Beitrag:
293-303
Nachgewiesen in:
Scopus; Web of Science
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1007/s00366-019-00824-y
Verlag / Institution:
Springer Science and Business Media LLC
Verlagsort:
New York, NY, USA
Print-ISSN:
0177-0667
E-ISSN:
1435-5663
Impact Factor:
7.963 (2020)
Copyright Informationen:
Copyright © 2019, Springer-Verlag London Ltd., part of Springer Nature. All rights reserved.
Format:
Text
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