首页|Findings from Loughborough University Broaden Understanding of Machine Learning (Predicting Restraining Effects In Cfs Channels: a Machine Learning Approach)
Findings from Loughborough University Broaden Understanding of Machine Learning (Predicting Restraining Effects In Cfs Channels: a Machine Learning Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news originating from Loughborough, United Kingdom, by NewsRx correspondents, research stated, “This paper aims to d evelop Machine Learning (ML) algorithms to predict the buckling resistance of co ld -formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckli ng behaviour of CFS channels subjected to pure axial compressive load or bending moment.”
LoughboroughUnited KingdomEuropeCy borgsEmerging TechnologiesMachine LearningLoughborough University
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