Investigating the efficiency of machine learning algorithms in classifying pulse-like ground motions
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geochemistry and Petrology,Geophysics
Link
https://link.springer.com/content/pdf/10.1007/s10950-023-10168-2.pdf
Reference94 articles.
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3. Alimoradi A, Beck JL (2015) Machine-learning methods for earthquake ground motion analysis and simulation. J Eng Mech 141(4):04014147. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000869
4. Alloghani M, Al-Jumeily D, Mustafina J, Hussain A, & Aljaaf AJ (2020) A systematic review on supervised and unsupervised machine learning algorithms for data science. Supervised and unsupervised learning for data science, 3–21. https://doi.org/10.1007/978-3-030-22475-2_1
5. Amari SI, Wu S (1999) Improving support vector machine classifiers by modifying kernel functions. Neural Netw 12(6):783–789. https://doi.org/10.1016/S0893-6080(99)00032-5
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