Employing the optimization algorithms with machine learning framework to estimate the compressive strength of ultra-high-performance concrete (UHPC)
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Mechanics of Materials,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s41939-023-00187-4.pdf
Reference50 articles.
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2. Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609. https://doi.org/10.1016/j.cma.2020.113609
3. Abualigah L, Almotairi KH, Elaziz MA, Shehab M, Altalhi M (2022) Enhanced flow direction arithmetic optimization algorithm for mathematical optimization problems with applications of data clustering. Eng Anal Bound Elem 138:13–29. https://doi.org/10.1016/j.enganabound.2022.01.014
4. Abuodeh OR, Abdalla JA, Hawileh RA (2020) Assessment of compressive strength of ultra-high performance concrete using deep machine learning techniques. Appl Soft Comput 95:106552
5. Agushaka JO, Ezugwu AE (2021) Advanced arithmetic optimization algorithm for solving mechanical engineering design problems. PLoS ONE 16(8):e0255703. https://doi.org/10.1371/journal.pone.0255703
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Explainable Ensemble Learning and Multilayer Perceptron Modeling for Compressive Strength Prediction of Ultra-High-Performance Concrete;Biomimetics;2024-09-09
2. Using Multiple Machine Learning Models to Predict the Strength of UHPC Mixes with Various FA Percentages;Infrastructures;2024-05-28
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