首页|New Findings on Machine Learning from Tongji University Summarized (Considering Creep In Rock Tunnelling With a Combined Support System: Theoretical Solutions a nd Machine-learning Solver)
New Findings on Machine Learning from Tongji University Summarized (Considering Creep In Rock Tunnelling With a Combined Support System: Theoretical Solutions a nd Machine-learning Solver)
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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 from Shanghai, People's Rep ublic of China, by NewsRx journalists, research stated, "This study provides an alternative theoretical approach to analyse the mechanical behaviour of tunnels excavated in time-dependent geomaterials, considering the sequential excavation of tunnels and installation of rockbolts and elastic liner. In the theoretical a nalyses, the Bolted Rock Mass (BRM) is modelled as a homogeneousmaterial but wi th higher stiffness."Funders for this research include National Natural Science Foundation of China ( NSFC), State KeyLaboratory of Disaster Reduction in Civil Engineering.
ShanghaiPeople's Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningTongji University
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