Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
EurekAlert!

Machine learning revolutionizes design of green solvents for carbon capture: a new era for ionic liquid development

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...
IEEE

Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...
Frontiers

Predictive modeling of airfoil aerodynamics via support vector machines

Forecasting aerodynamic coefficients of lift and drag is a crucial aspect of airfoil design and optimization in aerospace engineering. Among numerous desirable design features of the wing and/or ...
Scientific Research Publishing

Brereton, R.G. and Lloyd, G.R. (2010) Support Vector Machines for Classification and Regression. The Analyst, 135, 230-267.

ABSTRACT: Support vector regression (SVR) and computational fluid dynamics (CFD) techniques are applied to predict the performance of an automotive torque converter in the design process of turbine ...
Visual Studio Magazine

Linear Support Vector Regression Using C# with Particle Swarm Training

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...
IEEE

Solar Energy Forecasting Using Machine Learning Techniques for Enhanced Grid Stability

Abstract: The increasing integration of solar photovoltaic (PV) systems into modern energy grids presents significant challenges due to the intermittent and weather-dependent nature of solar energy ...
Visual Studio Magazine

Linear Support Vector Regression from Scratch Using C# with Evolutionary Training

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...
Frontiers

Regression-based machine learning models for nitrate and chloride prediction in surface water in a small agricultural sand plain sub-watershed in southwestern Ontario, Canada

Machine learning (ML) models have proven to be an efficient technique for better understanding and quantification of surface water quality, especially in agricultural watersheds where considerable ...
Scientific Research Publishing

Research on Credit Risk Rating of Commercial Banks Based on Support Vector Machine

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...