首页|Study Results from China Jiliang University in the Area of Support Vector Machin es Reported (A Fault Diagnosis Method for Ultrasonic Flow Meters Based On Kpca-c lssa-svm)
Study Results from China Jiliang University in the Area of Support Vector Machin es Reported (A Fault Diagnosis Method for Ultrasonic Flow Meters Based On Kpca-c lssa-svm)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Support Vector Machines have bee n presented. According to news originating from Hangzhou, People’s Republic of C hina, by NewsRx correspondents, research stated, “To enhance the fault diagnosis capability for ultrasonic liquid flow meters and refine the fault diagnosis acc uracy of support vector machines, we employ Levy flight to augment the global se arch proficiency. By utilizing circle chaotic mapping to establish the starting locations of sparrows and refining the sparrow position with the highest fitness value, we propose an enhanced sparrow search algorithm termed CLSSA.”
HangzhouPeople’s Republic of ChinaAs iaAlgorithmsEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesChina Jiliang University
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