2012
DOI: 10.1007/s13344-012-0002-8
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Artificial neural network ability in evaluation of random wave-induced inline force on a vertical cylinder

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Cited by 12 publications
(1 citation statement)
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“…Guo et al (2015) carried out hydrodynamic experiment of the extreme wave forces on the superstructure of coastal highway bridges, and proposed an estimation formula for calculating the extreme wave forces on such bridges. Lotfollahi-Yaghin et al (2012) established the relationship between wave force and liquid level fluctuation around vertical cylinder by using artificial neural network model, which was used for rapid prediction of wave load. Wei et al (2017) obtained the variation characteristics between the structural response and load parameters by conducting experimental research on the structural response of independent bridge towers under the action of wave-current load.…”
Section: Introductionmentioning
confidence: 99%
“…Guo et al (2015) carried out hydrodynamic experiment of the extreme wave forces on the superstructure of coastal highway bridges, and proposed an estimation formula for calculating the extreme wave forces on such bridges. Lotfollahi-Yaghin et al (2012) established the relationship between wave force and liquid level fluctuation around vertical cylinder by using artificial neural network model, which was used for rapid prediction of wave load. Wei et al (2017) obtained the variation characteristics between the structural response and load parameters by conducting experimental research on the structural response of independent bridge towers under the action of wave-current load.…”
Section: Introductionmentioning
confidence: 99%