Findings in Support Vector Machines Reported from Beijing JiaotongUniversity (M edium-term Wind Power Prediction Based On Lstm Classification Aided Pelt-neuralp rophet Hho-svm)
Findings in Support Vector Machines Reported from Beijing JiaotongUniversity (M edium-term Wind Power Prediction Based On Lstm Classification Aided Pelt-neuralp rophet Hho-svm)
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning - Support Vector Machines is the subject of a report. Accordingto news reporting originating in Beijing, People’s Republic of China, by NewsRx journalists, research stated,“T he precision of wind power prediction plays a vital role in ensuring the stable operation of wind powersystems. To elevate this accuracy and enhance the real-t ime performance, this paper proposes a hybridSupport Vector Machine (SVM) metho d, with using the Long Short-Term Memory Network (LSTM) tocategorize the wind d ata based on the statistical features and feedback to the trained SVM model.”
Key words
Beijing/People’s Republic of China/Asi a/Algorithms/Machine Learning/Support Vector Machines/Beijing Jiaotong University
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