Machine learning detects more than 60,000 earthquakes during 2025 Santorini sequence

The seismic crisis that gripped the Greek island of Santorini and its neighbors in 2025 contained more than 60,000 ...
EurekAlert!

New rapid battery-capacity estimation method could shorten lithium-ion cell grading

Researchers have developed a feature-enhanced ensemble learning method for rapidly estimating the capacity of lithium-ion ...
Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
EurekAlert!

FedPD: personalized federated learning based on partial distillation

Sub-headline: HIT (Shenzhen) researchers develop FedPD to enhance personalized cross-architecture collaboration  Researchers ...
Devdiscourse

Deep learning and AI unlock new era of solar energy forecasting and performance

Read more about Deep learning and AI unlock new era of solar energy forecasting and performance on Devdiscourse ...
Morning Overview on MSN

New AI model aims to improve seasonal drought forecasts

Federal scientists announced a new artificial intelligence tool that can forecast drought conditions 90 days ahead across the entire United States, marking a significant step in how the government ...
Scientific Research Publishing

Mienye, I.D. and Sun, Y. (2022) A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects. IEEE Access, 10, 99129-99149.

ABSTRACT: Prostate cancer remains one of the most prevalent malignancies among men worldwide and achieving an accurate and timely diagnosis is essential for guiding appropriate treatment decisions and ...
IEEE

Adaptive Honeypots using Reinforcement Learning Algorithms DQN and DDQN in Ensemble Framework: A Systematic Literature Review

Abstract: The exponential growth of sophisticated cyber threats has necessitated the evolution from traditional static honeypots to intelligent, adaptive deception systems. This systematic literature ...
financefeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
IEEE

Fall Risk Prediction Method Based on Human Electrostatic Field and Stacking Ensemble Learning Algorithm

Abstract: Accurate fall risk prediction is crucial for early intervention and prevention, effectively reducing the incidence of falls and the associated harm. This paper proposes a non-contact gait ...