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Review of challenges and opportunities in turbulence modeling: A comparative analysis of data-driven machine learning approaches
Engineering and scientific applications are frequently affected by turbulent phenomena,
which are associated with a great deal of uncertainty and complexity. Therefore, proper …
which are associated with a great deal of uncertainty and complexity. Therefore, proper …
Applications of particle swarm optimization in geotechnical engineering: a comprehensive review
Particle swarm optimization (PSO) is an evolutionary computation approach to solve
nonlinear global optimization problems. The PSO idea was made based on simulation of a …
nonlinear global optimization problems. The PSO idea was made based on simulation of a …
Prediction of water quality indexes with ensemble learners: Bagging and boosting
One of the most crucial jobs to improve water resources management plans is the
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streams
Discharge of pollution loads into natural water systems remains a global challenge that
threatens water and food supply, as well as endangering ecosystem services. Natural …
threatens water and food supply, as well as endangering ecosystem services. Natural …
Predicting seepage losses from lined irrigation canals using machine learning models
Introduction Efficient water resource management in irrigation systems relies on the accurate
estimation of seepage loss from lined canals. This study utilized machine learning (ML) …
estimation of seepage loss from lined canals. This study utilized machine learning (ML) …
Comparative assessment of individual and ensemble machine learning models for efficient analysis of river water quality
The prediction accuracies of machine learning (ML) models may not only be dependent on
the input parameters and training dataset, but also on whether an ensemble or individual …
the input parameters and training dataset, but also on whether an ensemble or individual …
A novel improved chef-based optimization algorithm with Gaussian random walk-based diffusion process for global optimization and engineering problems
The chef-based optimization algorithm (CBOA) is a human-based method inspired by the
relationship between culinary students and chef instructors. The original CBOA does not …
relationship between culinary students and chef instructors. The original CBOA does not …
An integrated trapezoidal fuzzy FUCOM with single-valued neutrosophic fuzzy MARCOS and GMDH method to determine the alternatives weight and its applications …
This paper aims to introduce the Trapezoidal Fuzzy-Full Consistency Approach-Single
Valued Neutrosophic Fuzzy-Measurement Alternatives and Ranking according to the …
Valued Neutrosophic Fuzzy-Measurement Alternatives and Ranking according to the …
Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design
Predicting the behavior and geometry of channels and alluvial rivers in which erosion and
sediment transport are in equilibrium is among the most important topics relating to river …
sediment transport are in equilibrium is among the most important topics relating to river …
Multi-expression programming (MEP): water quality assessment using water quality indices
Water contamination is indeed a worldwide problem that threatens public health,
environmental protection, and agricultural productivity. The distinctive attributes of machine …
environmental protection, and agricultural productivity. The distinctive attributes of machine …