[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
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 …
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
High-strength concrete (HSC) is a functional material possessing superior mechanical
performance and considerable durability, which has been widely used in long-span bridges …
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 …
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 …
steel reinforcement in reinforced concrete elements in corrosion areas. Shear resistance of …
State-of-art: artificial intelligence models era in modeling beam shear strength
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 …
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 …
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 …
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
In present work, prediction of the maximum loading carrying capacity of reactive powder
concrete and normal strength concrete column specimens using artificial neural networks …
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
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 …
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 …
adaptive regression spline (MARS), and random forest (RF) models for predicting the lead …