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Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings

Research article (Soil Dynamics and Earthquake Engineering, 2024) · cited 21× · AI/ML
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Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings

Summary

Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings is a scholarly article[1].

Key Facts

  • Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings. Retrieved May 24, 2026, from https://4ort.xyz/entity/proposing-unsupervised-clustering-based-earthquake-records-selection-framework-for-computationally-efficient-nonlinear-r
MLA “Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/proposing-unsupervised-clustering-based-earthquake-records-selection-framework-for-computationally-efficient-nonlinear-r.
BibTeX @misc{4ortxyz_proposing-unsupervised-clustering-based-earthquake-records-selection-framework-for-computationally-efficient-nonlinear-r_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Proposing unsupervised clustering-based earthquake records selection framework for computationally efficient nonlinear response history analysis of structures equipped with multi-stage friction pendulum bearings}}, year = {2026}, url = {https://4ort.xyz/entity/proposing-unsupervised-clustering-based-earthquake-records-selection-framework-for-computationally-efficient-nonlinear-r}, note = {Accessed: 2026-05-24}}
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