[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review

H Tao, MM Hameed, HA Marhoon… - Neurocomputing, 2022 - Elsevier
Developing accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …

Mechanical performance prediction for sustainable high-strength concrete using bio-inspired neural network

J Sun, J Wang, Z Zhu, R He, C Peng, C Zhang… - Buildings, 2022 - mdpi.com
High-strength concrete (HSC) is a functional material possessing superior mechanical
performance and considerable durability, which has been widely used in long-span bridges …

Prediction and feature analysis of punching shear strength of two-way reinforced concrete slabs using optimized machine learning algorithm and Shapley additive …

Y Wu, Y Zhou - Mechanics of Advanced Materials and Structures, 2023 - Taylor & Francis
Punching shear strength (PSS) is an important index for the design and analysis of two-way
reinforced concrete slabs. To accurately predict the PSS of two-way reinforced concrete …

Machine learning models development for shear strength prediction of reinforced concrete beam: a comparative study

ZM Yaseen - Scientific Reports, 2023 - nature.com
Fiber reinforced polymer (FPR) bars have been widely used as a substitutional material of
steel reinforcement in reinforced concrete elements in corrosion areas. Shear resistance of …

State-of-art: artificial intelligence models era in modeling beam shear strength

Z Al‐Khafaji, S Heddam, S Kim… - Knowledge …, 2022 - … journals.publicknowledgeproject.org
The computer aided models have received much attention in the recent years for solving
diverse civil engineering applications. In the current review, the applications of artificial …

Flood prediction using hybrid ANFIS-ACO model: a case study

A Agnihotri, A Sahoo, MK Diwakar - Inventive Computation and Information …, 2022 - Springer
Growing imperviousness and urbanization have increased peak flow magnitude which
results in flood events specifically during extreme conditions. Precise and reliable multi-step …

Research on prediction of compressive strength of fly ash and slag mixed concrete based on machine learning

M Wang, J Kang, W Liu, J Su, M Li - Plos One, 2022 - journals.plos.org
Every year, a large amount of solid waste such as fly ash and slag is generated worldwide. If
these solid wastes are used in concrete mixes to make concrete, it can effectively save …

Predicting of load carrying capacity of reactive powder concrete and normal strength concrete column specimens using artificial neural network

B Salman, MM Kadhum - Knowledge …, 2022 - … journals.publicknowledgeproject.org
In present work, prediction of the maximum loading carrying capacity of reactive powder
concrete and normal strength concrete column specimens using artificial neural networks …

Predictability performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid adaptive neuro-fuzzy system model

RM Adnan, ZM Yaseen, S Heddam, S Shahid… - International Journal of …, 2022 - Elsevier
Reliable modeling of river sediments transport is important as it is a defining factor of the
economic viability of dams, the durability of hydroelectric-equipment, river susceptibility to …

Prediction of lead (Pb) adsorption on attapulgite clay using the feasibility of data intelligence models

SK Bhagat, M Paramasivan, M Al-Mukhtar… - … Science and Pollution …, 2021 - Springer
This study investigates the performance of support vector machine (SVM), multivariate
adaptive regression spline (MARS), and random forest (RF) models for predicting the lead …