Ahmed Salih Mohammed

According to our database, Ahmed Salih Mohammed authored at least 11 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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., July, 2024

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., April, 2024

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., June, 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., March, 2023

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

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

Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance.

Jie Zeng, Bishwajit Roy, Deepak Kumar, Ahmed Salih Mohammed, Danial Jahed Armaghani, Jian Zhou, Edy Tonnizam Mohamad

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

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

Eng. Comput., 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

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