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The Whale Optimization Algorithm Based ANN for Predicting the Fundamental Period of Light-Frame Wood Buildings
The paper introduces the convenient and reliable method for the period estimate of wood buildings employing Artificial Neural Network (ANN) combined with Whale Optimization Algorithm (WOA). The algorithmic model developed using Feed Forward (FF) networks is based on the physical parameters of 47 light-frame wood buildings whose dynamic properties were measured using the ambient vibration testing method. The proposed model produces a better period estimate than the model available in the National Building Code of Canada (NBCC, 2015).
The Whale Optimization Algorithm Based ANN for Predicting the Fundamental Period of Light-Frame Wood Buildings
The paper introduces the convenient and reliable method for the period estimate of wood buildings employing Artificial Neural Network (ANN) combined with Whale Optimization Algorithm (WOA). The algorithmic model developed using Feed Forward (FF) networks is based on the physical parameters of 47 light-frame wood buildings whose dynamic properties were measured using the ambient vibration testing method. The proposed model produces a better period estimate than the model available in the National Building Code of Canada (NBCC, 2015).
The Whale Optimization Algorithm Based ANN for Predicting the Fundamental Period of Light-Frame Wood Buildings
Lecture Notes in Civil Engineering
Mendonça, Paulo (editor) / Cortiços, Nuno Dinis (editor) / Nikoo, M. (author) / Hafeez, G. (author)
International Conference on Architecture, Materials and Construction ; 2021 ; Lisbon, Portugal
Proceedings of the 7th International Conference on Architecture, Materials and Construction ; Chapter: 24 ; 230-236
2022-02-01
7 pages
Article/Chapter (Book)
Electronic Resource
English
Predicting the Fundamental Period of Light-Frame Wood Buildings
British Library Online Contents | 2014
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