Robotics & Machine Learning Daily News2024,Issue(Mar.14) :28-28.

Findings from University of Waterloo Reveals New Findings on Machine Learning (D evelopment of Explicit Models To Predict Methane Hydrate Equilibrium Conditions In Pure Water and Brine Solutions: a Machine Learning Approach)

Robotics & Machine Learning Daily News2024,Issue(Mar.14) :28-28.

Findings from University of Waterloo Reveals New Findings on Machine Learning (D evelopment of Explicit Models To Predict Methane Hydrate Equilibrium Conditions In Pure Water and Brine Solutions: a Machine Learning Approach)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating from Waterloo, Canada, b y NewsRx correspondents, research stated, “An important phase in the design of p rocesses involving gas hydrates is predicting the hydrate formation conditions. In this study, three explicit correlations based on machine learning techniques, gene expression programming (GEP), and optimizing two correlations with predete rmined structures were developed for the prediction of methane hydrate formation temperature (HFT) in pure water and brines.” Financial support for this research came from Natural Sciences and Engineering Research Council of Canada (NSERC).

Key words

Waterloo/Canada/North and Central America/Alkanes/Cyborgs/Emerging Technologies/Machine Learning/Methane/Univers ity of Waterloo

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文