首页|Data on Machine Learning Discussed by Researchers at Chongqing Jiaotong Universi ty (Machine-learning-aided Shear-capacity Solution of Rc Girders With Web Stirru ps Based On the Modified Compression Field Theory)
Data on Machine Learning Discussed by Researchers at Chongqing Jiaotong Universi ty (Machine-learning-aided Shear-capacity Solution of Rc Girders With Web Stirru ps Based On the Modified Compression Field Theory)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting originating from Chongqing, People's Republic of China, by NewsRx correspondents, research stated, "It is w idely recognized that critical crack angle theta is a pre-requisite to calculate the shear capacity of RC elements in traditional modified compression field the ory (MCFT), and it is often determined by an iterative calculation or by presupp osing an empirical value. This study proposes a straightforward solution of crit ical crack angle aided by machine learning."
ChongqingPeople's Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningChongqing Jiaotong Univer sity
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