Seismic-Induced Damage Localization Through Neural Networks and Clustring Method
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3397-2_59
Reference9 articles.
1. Bagheri A, Zare Hosseinzadeh A, Rizzo P, Ghodrati Amiri G (2017) Time domain damage localization and quantification in seismically excited structures using a limited number of sensors. JVC/J Vib Control 23:2942–2961. https://doi.org/10.1177/1077546315625141
2. Fung HSA, Vafaei M, Alih SC (2021) Effect of roof garden weight on the seismic fragility of relatively tall concrete wall buildings. Asian J Civ Eng 231(23):1–16. https://doi.org/10.1007/S42107-021-00405-9
3. Irfan Shirazi M, Khatir S, Benaissa B et al (2023) Damage assessment in laminated composite plates using modal Strain Energy and YUKI-ANN algorithm. Compos Struct 303:116272. https://doi.org/10.1016/J.COMPSTRUCT.2022.116272
4. Liu YY, Ju YF, Duan CD, Zhao XF (2011) Structure damage diagnosis using neural network and feature fusion. Eng Appl Artif Intell 24:87–92. https://doi.org/10.1016/j.engappai.2010.08.011
5. Umar S, Vafaei M, Alih SC (2021) Sensor clustering-based approach for structural damage identification under ambient vibration. Autom Constr 121:103433. https://doi.org/10.1016/j.autcon.2020.103433
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