Results 141 to 150 of about 605,737 (255)

A K-fold averaging cross-validation procedure

open access: yesJournal of nonparametric statistics (Print), 2015
Yoonsuh Jung, Jianhua Hu
semanticscholar   +1 more source

Accurate and Efficient Behavioral Modeling of GaN HEMTs Using An Optimized Light Gradient Boosting Machine

open access: yesAdvanced Theory and Simulations, EarlyView.
Machine Learning (ML) and optimization have permeated almost every aspect of engineering applications. Recent years have seen great traction toward ML‐based GaN HEMT modelling. However, ML‐based GaN HEMT models are mostly developed using variants of Artificial Neural Network (ANN).
Saddam Husain   +2 more
wiley   +1 more source

A New Method for Joint Sparse DOA Estimation. [PDF]

open access: yesSensors (Basel)
Hou J, Wang C, Zhao Z, Zhou F, Zhou H.
europepmc   +1 more source

Predicting Fiber Length Characteristics of Recycled Cotton and Cellulose Fiber Blends Using Machine Learning Models

open access: yesAdvanced Theory and Simulations, EarlyView.
This study explores machine learning‐driven prediction of fiber length characteristics in sustainable yarn blends made from recycled cotton and Lyocell. By analyzing empirical data through models like Random Forest and Gradient Boosting, and interpreting results with SHAP, key fiber length features from the Staple Diagram and Fibrogram are identified ...
Tuser Tirtha Biswas   +2 more
wiley   +1 more source

Role of the Setae in an Ectoparasitic Seal Louse in Reducing Surface Drag: Numerical Modeling Approach

open access: yesAdvanced Theory and Simulations, EarlyView.
The seal louse Echinophthirius horridus has uniquely shaped setae that may reduce drag during its host's dives. Using numerical simulations, this study demonstrates that their natural inclination promotes vortex formation, minimizing friction and energy loss. These findings provide insights into biological surface adaptations and may inspire the design
Anika Preuss   +3 more
wiley   +1 more source

Modeling Electrical Transport in Random Networks Composed of Metal‐Oxide Nanowires: The Transition from Junction‐Dominated to Nanowire‐Dominated Regime

open access: yesAdvanced Theory and Simulations, EarlyView.
This study proposes a model for the electrical transport properties of random networks of metal oxide nanowires. Based on the characteristic lengths and energies of nanowires, it allows for discussing the transition from the junction‐dominated to the nanowire‐dominated transport regime.
Andrea Ponzoni
wiley   +1 more source

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