Frontiers

Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
C&EN

Accelerating Catalysis Understanding via Large Language Model Data Extraction and Shallow Machine Learning Techniques

Department of Chemical & Petroleum Engineering, The University of Kansas, 4132 Learned Hall 1530 W 15th St, Lawrence, Kansas 66045, United States Center for Environmentally Beneficial Catalysis, The ...
IEEE

Inorganic Chemical Reaction Predictor Using Random Forest and Support Vector Machine

Abstract: The Chemical Reaction Predictor project shall use machine learning approaches to make predictions on chemical reaction effects. When a large enough group of known reactions is available, ...
Frontiers

Investigating pre-Columbian floristic legacy effects using machine learning in the southern Atlantic Forest, Brazil

The scope and scale of past human impacts on both historic and current vegetation is of widespread interest in the historical sciences. In the Atlantic Forest of southern Brazil (Portuguese: Mata ...
IEEE

An Improved Iterative Learning Control Approach Based on Random Forest and Whale Optimization for Urban Traffic Signals

Abstract: Iterative learning control (ILC) has demonstrated effectiveness in urban traffic signal control systems. However, conventional ILC methods typically require infinite iterations to achieve ...
C&EN

A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.