Results 201 to 210 of about 6,285,017 (364)

CLASV: Rapid Lassa virus lineage assignment with random forest. [PDF]

PLoS Negl Trop Dis
Daodu RO, Awotoro E, Ulrich JU, Kühnert D.   +3 more
europepmc   +1 more source

Machine Learning-Based Classification of Hybrid BCI Signals using Mayfly-Optimized Multiclass Weighted Random Forest

, 2023
R. Shelishiyah, Deepa Beeta Thiyam, M. Jehosheba Margaret   +2 more
openalex   +2 more sources

Ultra‐Improved Interfacial Strength Between Metallic Surface and Polyurethane via Cost‐Effective Anodizing Process

Advanced Materials Interfaces, EarlyView.
SAA significantly enhanced Al/PU bonding, increasing SLSS by up to 920% and fracture energy by 15 100% through optimized micro‐nano porous surfaces. RSM identified the optimal anodizing conditions, while ML confirmed sulfuric acid concentration and roughness as dominant predictors of strength.
Umut Bakhbergen, Sherif Araby, Zhandos Tauanov, Nursultan Turdakyn, Reza Montazami, Fethi Abbassi, Gulnur Kalimuldina   +6 more
wiley   +1 more source

Laser-printed document classification using random forest and gray prediction models. [PDF]

iScience
Qu Y, Yu C, Li C, Yang Y.
europepmc   +1 more source

AI‐Enhanced Gait Analysis Insole with Self‐Powered Triboelectric Sensors for Flatfoot Condition Detection

Advanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
The given research presents an innovative insole‐based device employing self‐powered triboelectric nanogenerators (TENG) for flatfoot detection. By integrating TENG tactile sensors within an insole, the device converts mechanical energy from foot movements to electrical signals analyzed via machine learning, achieving an 82% accuracy rate in flatfoot ...
Moldir Issabek, Sabyrzhan Oralkhan, Adeliya Anash, Nuriya Nurbergenova, Azat Balapan, Azamat Yeshmukhametov, Yeltay Rakhmanov, Gulnur Kalimuldina   +7 more
wiley   +1 more source

Real time urban traffic prediction using RFID and a hybrid LSTM random forest model. [PDF]

Sci Rep
Khattab O, Saravana Balaji B, Alghadhoori F, AlMazyad F, AlDousari M, Al-Ameeri A, Al-Kadri MO.   +6 more
europepmc   +1 more source

Random Forest

The Journal of The Institute of Image Information and Television Engineers, 2012
openaire   +2 more sources

Random Forests model selection

, 2016
Random Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have shown to be effective in many different real world classification problems and nowadays are considered as one of the best learning algorithms in this context.
ORLANDI, ILENIA, ONETO, LUCA, ANGUITA, DAVIDE   +2 more
openaire   +2 more sources

Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest

SN Applied Sciences, 2020
E. Şahin
semanticscholar   +1 more source

Spider Silk–Integrated Biomimetic Micropillars With Dual Adhesion for Improved Wound Hemostasis and Healing

Advanced Materials Technologies, EarlyView.
The patch mimics the dual physicochemical adhesion mechanisms of gecko toe micropillars and spider silk proteins, enabling strong interfacial bonding via partially cured micropillars. Its facile fabrication allows customization for precision medicine, while its motion responsiveness offers potential for real‐time wound monitoring.
Chengxin Luan, Meng Wei, Xinran Chen, Ni Gan, Bingbing Gao   +4 more
wiley   +1 more source