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ORCIDAhmed Salih Mohammed
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2020 – today
- 2024
[j11]Aso A. Abdalla, Ahmed Salih Mohammed
:
The efficiency of hybrid intelligent models to evaluate the effect of the size of sand and clay metakaolin content on various compressive strength ranges of cement mortar. Neural Comput. Appl. 36(11): 6209-6229 (2024)- [j10]Hunar Farid Hama Ali, Bashdar Omer, Ahmed Salih Mohammed, Rabar H. Faraj:
Predicting the maximum dry density and optimum moisture content from soil index properties using efficient soft computing techniques. Neural Comput. Appl. 36(19): 11339-11369 (2024) - 2023
- [j9]Hemn Unis Ahmed, Reham R. Mostafa, Ahmed Salih Mohammed, Parveen Sihag, Azad Qadir:
Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete. Neural Comput. Appl. 35(3): 2909-2926 (2023) - [j8]Hemn Unis Ahmed, Ahmed Salih Mohammed, Rabar H. Faraj, Aso A. Abdalla, Shaker M. A. Qaidi, Nadhim Hamah Sor, Azad A. Mohammed:
Innovative modeling techniques including MEP, ANN and FQ to forecast the compressive strength of geopolymer concrete modified with nanoparticles. Neural Comput. Appl. 35(17): 12453-12479 (2023) - [j7]Wael Mahmood, Ahmed Salih Mohammed, Panagiotis G. Asteris, Hawreen Ahmed:
Soft computing technics to predict the early-age compressive strength of flowable ordinary Portland cement. Soft Comput. 27(6): 3133-3150 (2023) - 2022
- [j6]Mahdi Hasanipanah, Mehdi Jamei, Ahmed Salih Mohammed, Menad Nait Amar, Hocine Ouaer, Khaled Mohamed Khedher:
Intelligent prediction of rock mass deformation modulus through three optimized cascaded forward neural network models. Earth Sci. Informatics 15(3): 1659-1669 (2022) - [j5]Jiandong Huang, Panagiotis G. Asteris, Siavash Manafi Khajeh Pasha, Ahmed Salih Mohammed, Mahdi Hasanipanah:
A new auto-tuning model for predicting the rock fragmentation: a cat swarm optimization algorithm. Eng. Comput. 38(3): 2209-2220 (2022) - [j4]Mingxiang Cai, Hocine Ouaer, Ahmed Salih Mohammed, Xiaoling Chen, Menad Nait Amar, Mahdi Hasanipanah:
Integrating the LSSVM and RBFNN models with three optimization algorithms to predict the soil liquefaction potential. Eng. Comput. 38(4): 3611-3623 (2022) - [j3]Jie Zeng, Bishwajit Roy, Deepak Kumar, Ahmed Salih Mohammed, Danial Jahed Armaghani, Jian Zhou, Edy Tonnizam Mohamad:
Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance. Eng. Comput. 38(5): 3811-3827 (2022) - [j2]Jing Cao, Juncheng Gao, Hima Nikafshan Rad, Ahmed Salih Mohammed, Mahdi Hasanipanah, Jian Zhou:
A novel systematic and evolved approach based on XGBoost-firefly algorithm to predict Young's modulus and unconfined compressive strength of rock. Eng. Comput. 38(5): 3829-3845 (2022) - [j1]Hemn Unis Ahmed, Ahmed Salih Mohammed, Azad A. Mohammed:
Multivariable models including artificial neural network and M5P-tree to forecast the stress at the failure of alkali-activated concrete at ambient curing condition and various mixture proportions. Neural Comput. Appl. 34(20): 17853-17876 (2022)
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