首页|New Findings on Support Vector Machines from Beijing Jiaotong University Summarized (A Dynamic Stiffness-based Two-step Method for Damage Identification of Joints In Hinged Slab Bridges Using Support Vector Machine)
New Findings on Support Vector Machines from Beijing Jiaotong University Summarized (A Dynamic Stiffness-based Two-step Method for Damage Identification of Joints In Hinged Slab Bridges Using Support Vector Machine)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Support Vector Machines. According to newsoriginating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Ascritical components of hinged slab bridges, joints are of great importance to the bearing capacity andserviceability of bridges. The existing model-based joint damage detection methods are based on precisefinite element models, and their identification accuracy is significantly affected by construction uncertainty.”
BeijingPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesBeijing Jiaotong University
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