Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
Risk.net

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...
The Southern Maryland Chronicle on MSN

How are QA teams using machine learning to predict test failures in real time?

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Fentanyl or phony? Machine learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
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 ...
Search Engine Land

Google algorithm updates 2025 in review: 3 core updates and 1 spam update

Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then ...
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, ...
Scientific Research Publishing

Breiman, L. (2001) Random Forests. Machine Learning, 45, 5-32.

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
IEEE

Machine Learning Approaches for Banana Quality Classification: A Performance Comparison of J48 and Random Forest Algorithms

Abstract: This study evaluates the performance of using machine learning models; J48 and Random Forest to classify bananas quality. The existing methods of visual inspection are qualitative and take ...
Scientific Research Publishing

Breiman, L. (2001) Random Forests. Machine Learning, 45, 5-32.

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...