S. I. Abba

A Large Language Model-based Generative Artificial Intelligence and hybrid machine learning framework for prediction and inverse design of jute fiber concrete

Generative data augmentation, explainable machine learning, and uncertainty analysis for compressive strength prediction of sustainable UHPC

Recent interest in ultra-high-performance concrete (UHPC) has been on the use of construction and demolition waste (CDW) due to the growing need to use sustainable construction materials. Recycled concrete powder (RCP), a product of CDW, is a promising way to reduce cement use, lower CO 2 emissions, and make green cons...

Environmentally informed prediction of ultimate bearing capacity using Kernel-SVM and PLAXIS 3D FEM for sustainable geotechnical design

Accurately predicting Ultimate Bearing Capacity (UBC) is crucial for the safe and efficient design of foundations in geotechnical engineering. Yet, traditional methods remain time-consuming, costly, and environmentally disruptive. This study applies Support Vector Machine (SVM) models to develop a data-driven predictiv...

Transfer-learned stacked models for assessing mechanical and environmental properties of glass powder UHPC