Walaa Hussein Ali AL Yamani

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Civil and Structural Engineering, General Materials Science, Mechanics of Materials

Scopus Publications

Machine learning in seismic structural design: an exploration of ANN and tabu-search optimization
Walaa Hussein Al Yamani, Majdi Bisharah, Huthaifa Hussein Alumany, Nour Abedalaziz Al Mohammadin
Asian Journal of Civil Engineering, 2024
Comprehensive Assessment of Various Soft-Computing Models in Predicting the Load-Bearing Capacity of Concrete-Filled Steel Tube Columns
Jafar Al Thawabteh, Jamal Al Adwan, Walaa Al Yamani, Bilal Yasin, Yazan Alzubi
International Review on Modelling and Simulations, 2024
Nowadays, a concrete-filled steel tube column is considered a widely used section in the construction industry thanks to its high strength-to-weight ratio and ability to resist lateral loads. Recently, the use of concrete-filled steel tubes in composite structures has increased considerably due to their ability to withstand concentric compressive loads effectively while maintaining high ductility after yielding. These advantages are attributed to the combination of the properties of concrete and steel. Therefore, accurate estimation of their performance is essential for ensuring the safety and stability of structures. One approach to simply and rapidly predicting this is adopting soft computing techniques. Accordingly, this paper investigates the effectiveness of many soft computing techniques, including machine learning and regularized regression models, in predicting the capacity of rectangular concrete-filled steel tube columns. As part of the study, the results of the developed models will be compared against those of previous experimental works. Finally, the most accurate model will be recommended for utilization in such applications.
Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods
Walaa Hussein Al Yamani, Dalin Mohammad Ghunimat, Majdi Mowafaq Bisharah
Asian Journal of Civil Engineering, 2023
Correction: Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods (Asian Journal of Civil Engineering, (2023), 10.1007/s42107-023-00614-4)
Walaa Hussein Al Yamani, Dalin Mohammad Ghunimat, Majdi Mowafaq Bisharah
Asian Journal of Civil Engineering, 2023

RECENT SCHOLAR PUBLICATIONS

Machine learning in seismic structural design: An exploration of ann and tabu-search optimization
WH Al Yamani, M Bisharah, HH Alumany, NA Al Mohammadin
Asian Journal of Civil Engineering 25 (3), 2367-2377 , 2024
2024
Citations: 21
Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods
WH Al Yamani, DM Ghunimat, MM Bisharah
Asian Journal of Civil Engineering 24 (7), 1943-1955 , 2023
2023
Citations: 38
Correction: Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods
WH Al Yamani, DM Ghunimat, MM Bisharah
Asian Journal of Civil Engineering 24 (6), 1897-1897 , 2023
2023
Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods
WH Al Yamani, DM Ghunimat, MM Bisharah
Asian Journal of Civil Engineering 24 (7), 1943-1955 , 2023
2023
Citations: 38
Machine learning in seismic structural design: An exploration of ann and tabu-search optimization
WH Al Yamani, M Bisharah, HH Alumany, NA Al Mohammadin
Asian Journal of Civil Engineering 25 (3), 2367-2377 , 2024
2024
Citations: 21
Correction: Modeling and predicting the sensitivity of high-performance concrete compressive strength using machine learning methods
WH Al Yamani, DM Ghunimat, MM Bisharah
Asian Journal of Civil Engineering 24 (6), 1897-1897 , 2023
2023
Citations: 2