首页|Xinjiang Agricultural University Researcher Updates Current Data on Support Vect or Machines (Inversion Study on Landslide Seepage Field Based on Swarm Intellige nce Optimization Least-Square Support Vector Machine Algorithm)
Xinjiang Agricultural University Researcher Updates Current Data on Support Vect or Machines (Inversion Study on Landslide Seepage Field Based on Swarm Intellige nce Optimization Least-Square Support Vector Machine Algorithm)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Researchers detail new data in . According to new s originating from Urumqi, People’s Republic ofChina, by NewsRx correspondents, research stated, “The permeability coefficient of landslide mass, a keyparamet er in the study of reservoir landslides, is commonly obtained through in situ an d laboratory tests;however, the tests are costly and subject to high variabilit y, leading to potential biases. In this paper,a new method was proposed to inve rsely estimate the permeability coefficient of landslide layers usingmonitoring data of groundwater level (GWL).”
Xinjiang Agricultural UniversityUrumqiPeople’s Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine L earningSupport Vector MachinesSwarm IntelligenceVector Machines
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