首页|Studies from Saarland University Yield New Information about Machine Learning (I mproved Carbide Volume Fraction Estimation In As-cast Hcci Alloys Using Machine Learning Techniques)
Studies from Saarland University Yield New Information about Machine Learning (I mproved Carbide Volume Fraction Estimation In As-cast Hcci Alloys Using Machine Learning Techniques)
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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 originating from Saarbrucken, Germany, by News Rx correspondents, research stated, "An improved approach is presented for the e stimation of carbide volume fraction (CVF) in as-cast High Chromium Cast Iron (H CCI) alloys using Machine Learning (ML) techniques." Financial supporters for this research include German Research Foundation (DFG), EFRE Funds of the European Commission, State Chancellery of Saarland. Our news journalists obtained a quote from the research from Saarland University , "The limitations of existing formulae for CVF estimation in HCCI alloys, which relied on a limited number of alloy compositions, are addressed."
SaarbruckenGermanyEuropeAlloysCy borgsEmerging TechnologiesMachine LearningSaarland University
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