EurekAlert!

Energy learning hyper-heuristic algorithm for cooperative task assignment of heterogeneous UAVs under complex constraints

The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...
IEEE

Constraint-Guided Online Data Selection for Scalable Data-Driven Safety Filters in Uncertain Robotic Systems

Abstract: As the use of autonomous robots expands in tasks that are complex and challenging to model, the demand for robust data-driven control methods that can certify safety and stability in ...
Targeted Oncology

Machine Learning Model May Optimize Treatment Selection and Survival in HCC

The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...
GitHub

An AutoML framework for classical machine learning algorithms, automating model selection and hyperparameter tuning through Bayesian optimization, portfolio-based meta-learning ...

Start a Ray head node Connect and start Ray worker nodes via SSH Activate virtual environments and configure PYTHONPATH on all nodes 📌 Before running the script, ensure passwordless SSH access from ...
Frontiers

Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field

Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...
Frontiers

Optimized wavelength selection for eggplant seed vitality classification using information acquisition techniques

Eggplant seed vigor is a crucial indicator of its germination rate and seedling growth quality. In response to the need for efficient and nondestructive assessment methods, this study explores the use ...
IEEE

Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study

Abstract: The emergence of machine learning (ML) has led to a transformative shift in software techniques and guidelines for building software applications that support data analysis process ...