首页|Research Data from Fuzhou University Update Understanding of Support Vector Mach ines (Fault Section Location In Resonant Grounding Distribution Systems Based On Feature Subset Optimization of Phase Current Variation)
Research Data from Fuzhou University Update Understanding of Support Vector Mach ines (Fault Section Location In Resonant Grounding Distribution Systems Based On Feature Subset Optimization of Phase Current Variation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Support Vector Machines are discussed in a new report. According to news reporting originating from Fuzhou, People’s Republic of China, by NewsRx correspondents, research stated, “The exis ting single-phase grounding (SPG) fault section location methods typically suffe r from difficulty in feature selection, limited feeder terminal units (FTUs) con figuration, and excessive dependence on communication, which weaken their genera lization and robustness. To overcome these challenges, an SPG fault section loca tion approach based on feature subset optimization is proposed.”
FuzhouPeople’s Republic of ChinaAsiaAlgorithmsEmerging TechnologiesGenetic AlgorithmsMachine LearningSuppo rt Vector MachinesVector MachinesFuzhou University
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