Intelligent prediction of rock mass deformation modulus through three optimized cascaded forward neural network models. - Mahdi Hasanipanah; Mehdi Jamei; Ahmed Salih Mohammed; Menad Nait Amar; Hocine Ouaer; Khaled Mohamed Khedher (Earth Sci. Informatics, 2022)

Integrating the LSSVM and RBFNN models with three optimization algorithms to predict the soil liquefaction potential. - Mingxiang Cai; Hocine Ouaer; Ahmed Salih Mohammed; Xiaoling Chen; Menad Nait Amar; Mahdi Hasanipanah (Eng. Comput., 2022)

A novel systematic and evolved approach based on XGBoost-firefly algorithm to predict Young's modulus and unconfined compressive strength of rock. - Jing Cao; Juncheng Gao; Hima Nikafshan Rad; Ahmed Salih Mohammed; Mahdi Hasanipanah; Jian Zhou 007 (Eng. Comput., 2022)

A new auto-tuning model for predicting the rock fragmentation: a cat swarm optimization algorithm. - Jiandong Huang; Panagiotis G. Asteris; Siavash Manafi Khajeh Pasha; Ahmed Salih Mohammed; Mahdi Hasanipanah (Eng. Comput., 2022)

Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance. - Jie Zeng; Bishwajit Roy; Deepak Kumar 009; Ahmed Salih Mohammed; Danial Jahed Armaghani; Jian Zhou 007; Edy Tonnizam Mohamad (Eng. Comput., 2022)

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. - Hemn Unis Ahmed; Ahmed Salih Mohammed; Azad A. Mohammed (Neural Comput. Appl., 2022)

Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete. - Hemn Unis Ahmed; Reham R. Mostafa; Ahmed Salih Mohammed; Parveen Sihag; Azad Qadir (Neural Comput. Appl., 2023)

Soft computing technics to predict the early-age compressive strength of flowable ordinary Portland cement. - Wael Mahmood; Ahmed Salih Mohammed; Panagiotis G. Asteris; Hawreen Ahmed (Soft Comput., 2023)

Innovative modeling techniques including MEP, ANN and FQ to forecast the compressive strength of geopolymer concrete modified with nanoparticles. - Hemn Unis Ahmed; Ahmed Salih Mohammed; Rabar H. Faraj; Aso A. Abdalla; Shaker M. A. Qaidi; Nadhim Hamah Sor; Azad A. Mohammed (Neural Comput. Appl., 2023)

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. - Aso A. Abdalla; Ahmed Salih Mohammed (Neural Comput. Appl., 2024)

Predicting the maximum dry density and optimum moisture content from soil index properties using efficient soft computing techniques. - Hunar Farid Hama Ali; Bashdar Omer; Ahmed Salih Mohammed; Rabar H. Faraj (Neural Comput. Appl., 2024)