Application of Machine Learning Techniques to Predict Unconfined Compressive Strength of Sedimentary Rocks in UAE
Hussain Salah(University of Sharjah), Mohamed G. Arab(Mansoura University), Khaled Hamad(University of Sharjah), Maher Omar(University of Sharjah), Emran Alotaibi(Khalifa University of Science and Technology)
Cited by 4
Related Papers
Artificial intelligence in environmental monitoring: in-depth analysis
|Discover Artificial Intelligence|2024|144
Life cycle assessment of biocemented sands using enzyme induced carbonate precipitation (EICP) for soil stabilization applications
|Scientific Reports|2022|64
Prediction of Punching Shear Capacity for Fiber-Reinforced Concrete Slabs Using Neuro-Nomographs Constructed by Machine Learning
|Journal of Structural Engineering|2021|43
Optimizing the Compressive Strength of Sodium Alginate-Modified EICP-Treated Sand Using Design of Experiments
|Journal of Materials in Civil Engineering|2024|36
Geogrid bridging over existing shallow flexible PVC buried pipe – Experimental study
|Tunnelling and Underground Space Technology|2021|30