首页|Researchers from Dalian University of Technology Provide Details of New Studies and Findings in the Area of Support Vector Machines (Prediction of Depth-averaged Velocity for Flow Though Submerged Vegetation Using Least Squares Support Vector ...)
Researchers from Dalian University of Technology Provide Details of New Studies and Findings in the Area of Support Vector Machines (Prediction of Depth-averaged Velocity for Flow Though Submerged Vegetation Using Least Squares Support Vector ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Support Vector Machines have been published. According to news reporting from Dalian, People's Republic of China, by NewsRx journalists, research stated, "Considering the limited accuracy of classical empirical formulas and traditional Machine Learning (ML) models for predicting the depth-averaged velocity of flow through submerged vegetation, in this article, a novel hybrid ML model named BO-LSSVM is developed that incorporates Bayesian Optimization (BO) into Least Squares Support Vector Machine (LSSVM). Comparing with standalone LSSVM, BO helps LSSVM to find the optimal hyperparameter combination and thus promotes its prediction accuracy." Financial supporters for this research include National Natural Science Foundation of China (NSFC), National Natural Science Foundation of China (NSFC).
DalianPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesDalian University of Technology
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