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Adam M Root: How to use machine learning to reduce costs and boost output

Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...
TMCnet

Stony Brook University Develops Machine Learning Models that Predict PV System Underperformance on Heterogeneous Portfolios

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...
Chromatography Online

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Wastewater Digest

How digital twins position wastewater facilities for evolving challenges

Machine learning, AI, automation and and prediction are rapidly evolving the digital landscape. Can digital twins be the ...
Frontiers

Digital innovations in bioprocess optimization: The role of AI, machine learning, and digital twins

Bioprocess modeling is undergoing a transformative phase with the advent of digital technologies like artificial intelligence (AI) and machine learning ...
EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Rochester Institute of Technology

OLA'2024 International Conference on Optimization & Learning

The International Conference in Optimization and Learning (OLA2024), organized by RIT (Croatia) and the University of Lille (France), focuses on the future challenges of optimization and learning ...