A Hybrid Particle Swarm Optimization with Dragonfly for Adaptive ANFIS to Model the Corrosion Rate in Concrete Structures
Autor(en): |
Gholam Reza Khayati
Zahra Rajabi Maryam Ehteshamzadeh Hadi Beirami |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | International Journal of Concrete Structures and Materials, Dezember 2022, n. 1, v. 16 |
DOI: | 10.1186/s40069-022-00517-9 |
Abstrakt: |
The use of reinforced concrete is common in marine structures. Failure of reinforcement due to corrosion has detrimental impacts on nearly all of these structures. Hence, proposing an accurate and reliable model was imperative. The goal of this paper is to develop a new hybrid model by combining Particle Swarm Optimization (PSO) with Dragonfly Algorithm (DA) for Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the corrosion current density (C11) of marine reinforced concrete. The neuro-fuzzy-based methods have emerged as suitable techniques for encountering uncertainties associated with the corrosion phenomenon in marine structures. To the best of our knowledge, this is the first research that predicts the |
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Datenseite - Reference-ID
10746198 - Veröffentlicht am:
04.12.2023 - Geändert am:
04.12.2023