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Title:

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

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
Artificial neural network (ANN); Scour; Bridge pier; Particle swarm optimization (PSO); Levenberg–Marquardt algorithm (LM); Firefly algorithm (FA)
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Journal title:
Engineering with Computers
Year:
2021
Journal volume:
Vol. 37
Journal issue:
1
Pages contribution:
293-303
Covered by:
Scopus; Web of Science
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1007/s00366-019-00824-y
Publisher:
Springer Science and Business Media LLC
Publisher address:
New York, NY, USA
Print-ISSN:
0177-0667
E-ISSN:
1435-5663
Impact Factor:
7.963 (2020)
Copyright statement:
Copyright © 2019, Springer-Verlag London Ltd., part of Springer Nature. All rights reserved.
Format:
Text
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