首页|Reports Outline Support Vector Machines Study Findings from North China Electric Power University (An Advanced Quantum Support Vector Machine for Power Quality Disturbance Detection and Identification)
Reports Outline Support Vector Machines Study Findings from North China Electric Power University (An Advanced Quantum Support Vector Machine for Power Quality Disturbance Detection and Identification)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Research findings on Support Vector Machines are discussed in a new report. According tonews reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, researchstated, “Quantum algorithms have demonstrated extraordinary potential across numerous fields, of feringsignificant advantages in solving practical problems. Power Quality Distu rbances (PQDs) have always beena critical factor affecting the stability and sa fety of electrical power systems, and accurately detecting andidentifying PQDs is crucial for ensuring reliable system operation.”
BeijingPeople’s Republic of ChinaAsi aAlgorithmsEmerging TechnologiesMachine LearningQuantum AlgorithmSuppo rt Vector MachinesVector MachinesNorth China Electric Power University
NETL
NSTL
