Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review

S Wang, P Xia, K Chen, F Gong, H Wang… - Journal of Building …, 2023 - Elsevier
Among the many sustainability challenges in the construction industry, those related to the
application of concrete and its components are the most critical. Particularly, the production …

Preparation and application of multi-source solid wastes as clean aggregates: A comprehensive review

J Wang, H Dong - Construction and Building Materials, 2024 - Elsevier
Fully utilizing regional resources such as marine sand, coral, and desert sand, along with a
diverse range of solid wastes from industries, agriculture, and urban areas, not only …

A comprehensive study of various regressions and deep learning approaches for the prediction of friction factor in mobile bed channels

A Bassi, AA Mir, B Kumar, M Patel - Journal of Hydroinformatics, 2023 - iwaponline.com
A fundamental issue in the hydraulics of movable bed channels is the measurement of
friction factor (λ), which represents the head loss because of hydraulic resistance. The …

Prognosis of flow of fly ash and blast furnace slag-based concrete: leveraging advanced machine learning algorithms

R Kumar, A Rathore, R Singh, AA Mir, RK Tipu… - Asian Journal of Civil …, 2024 - Springer
In the field of construction, the workability of concrete, specifically its ability to flow, is one of
the most concerned parameters. In recent times, the integration of artificial intelligence (AI) …

Machine learning approaches for adequate prediction of flow resistance in alluvial channels with bedforms

AA Mir, M Patel - Water Science & Technology, 2024 - iwaponline.com
In natural rivers, flow conditions are mainly dependent on flow resistance and type of
roughness. The interactions among flow and bedforms are complex in nature as bedform …

Research on Urban Storm Flood Simulation by Coupling K-means Machine Learning Algorithm and GIS Spatial Analysis Technology into SWMM Model

C Liu, C Hu, C Zhao, Y Sun, T Xie, H Wang - Water Resources …, 2024 - Springer
Accurate flood simulation has significant practical implications for urban flood management.
The focus of this study is to develop a new flood model (K-SWMMG) based on the Storm …

Predictive Modelling of Flexural Strength in Recycled Aggregate-Based Concrete: A Comprehensive Approach with Machine Learning and Global Sensitivity Analysis

R Singh, RK Tipu, AA Mir, M Patel - Iranian Journal of Science and …, 2024 - Springer
This research focuses on predicting Flexural Strength (F ck) in recycled aggregate-based
concrete through a comprehensive approach integrating machine learning models and …

Experimental investigation on trinary blended geopolymer mortar synthesized from Industrial-agro and municipal solid waste ash subjected to different acid exposure

B Tipraj, T Shanmugapriya - Materials Research Express, 2023 - iopscience.iop.org
Geopolymer binders prove to be a reliable option to avoid dependency on conventional
binders, and reduce the burden on the environment. The current study assesses the …

[PDF][PDF] corrected Proof

AA Mir, M Patel - 2024 - researchgate.net
In natural rivers, flow conditions are mainly dependent on flow resistance and type of
roughness. The interactions among flow and bedforms are complex in nature as bedform …