自然科学版 英文版
自然科学版 英文版
自然科学版 英文版

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中南大学学报(英文版)

Journal of Central South University

Vol. 26    No. 11    November 2019

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Modified imperialist competitive algorithm-based neural network to determine shear strength of concrete beams reinforced with FRP
Amir HASANZADE-INALLU1, Panam ZARFAM2, Mehdi NIKOO3

1. Department of Earthquake Engineering, Science and Research Branch, Islamic Azad University,Tehran, Iran;
2. Department of Structural Engineering, Science and Research Branch, Islamic Azad University,Tehran, Iran;
3. Young Researchers and Elite Club, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

Abstract:Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest; however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.

 

Key words: concrete shear strength; fiber reinforced polymer (FRP); artificial neural networks (ANNs); Levenberg-Marquardt algorithm; imperialist competitive algorithm (ICA)

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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