Using Machine Learning Data to Achieve Sustainability, Performance and Governance Goals

In an environment defined by labor shortages, rising uptime expectations and pressure to improve overall equipment effectiveness (OEE), simple data collection is no longer enough.
EurekAlert!

Machine learning advances non targeted detection of environmental pollutants

A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...
Devdiscourse

AI and machine learning drive digital transformation across global mining operations

Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...
American Institute of Physics

Peering inside the machine learning black box for fusion experiments

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.
EurekAlert!

AI-optimized decision-making in energy systems: a new approach to integrating machine learning and mathematical programming

Discover how a new AI system is revolutionizing energy management by merging machine learning and mathematical programming. This innovative approach not only boosts prediction accuracy but also ...
Chromatography Online

AI/ML in Practice: Boudewijn Hollebrands on Deep Learning Models to Predict Food Peptide Retention Times

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...