Zainab Hasan Ali

TL;DR: New hybrid artificial intelligence model called integrative support vector regression with firefly optimization algorithm (SVR-FFA) for shear strength prediction of steel fiber-reinforced concrete beam (SFRCB) is attempted.

TL;DR: The developed hybrid RF-GA model revealed a good resultant performance in terms of accuracy, kappa and classification error, and indicated a robust and reliable technique for project delay prediction that is contributing to the construction project management monitoring and sustainability.

TL;DR: The proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

TL;DR: The hydrological process has a dynamic nature characterised by randomness and complex phenomena, and the application of machine learning (ML) models in forecasting river flow has grown rapidly.

TL;DR: In this article, the capacity of deep learning neural network (DLNN) for shear strength prediction of Perfobond Rib Shear Strength Connector (PRSC) is investigated, and the proposed DLNN model is validated against support vector regression (SVR), ANN, and M5 tree model.