首页|Study Findings from Los Alamos National Laboratory Provide New Insights into Machine Learning (Machine Learning Based Approach To Predict Ductile Damage Model Parameters for Polycrystalline Metals)
Study Findings from Los Alamos National Laboratory Provide New Insights into Machine Learning (Machine Learning Based Approach To Predict Ductile Damage Model Parameters for Polycrystalline Metals)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is the subject of a report. According to newsreporting originating in Los Alamos, New Mexico, by NewsRx journalists, research stated, “Damage modelsfor ductile materials typically need to be parameterized, often with the appropriate parameters changingfor a given material depending on the loading conditions. This can make parameterizing these modelscomputationally expensive, since an inverse problem must be solved for each loading condition.”
Los AlamosNew MexicoUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningLos Alamos National Laboratory
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