The Whale Optimization Algorithm Based ANN for Predicting the Fundamental Period of Light-Frame Wood Buildings

M. Nikoo, G. Hafeez*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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).

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Architecture, Materials and Construction - ICAMC 2021
EditorsPaulo Mendonça, Nuno Dinis Cortiços
PublisherSpringer Science and Business Media Deutschland GmbH
Pages230-236
Number of pages7
ISBN (Print)9783030945138
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event7th International Conference on Architecture, Materials and Construction, ICAMC 2021 - Virtual, Online
Duration: Oct 27 2021Oct 29 2021

Publication series

NameLecture Notes in Civil Engineering
Volume226 LNCE
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference7th International Conference on Architecture, Materials and Construction, ICAMC 2021
CityVirtual, Online
Period10/27/2110/29/21

Keywords

  • Feed forward
  • Neural network
  • Period formula
  • Whale optimization
  • Wood buildings

ASJC Scopus subject areas

  • Civil and Structural Engineering

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