• Title/Summary/Keyword: 하이브리드 최소제곱 Support Vector Machine

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Prediction Performance of Hybrid Least Square Support Vector Machine with First Principle Knowledge (First Principle을 결합한 최소제곱 Support Vector Machine의 예측 능력)

  • 김병주;심주용;황창하;김일곤
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.744-751
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    • 2003

  • A hybrid least square Support Vector Machine combined with First Principle(FP) knowledge is proposed. We compare hybrid least square Support Vector Machine(HLS-SVM) with early proposed models such as Hybrid Neural Network(HNN) and HNN with Extended Kalman Filter(HNN-EKF). In the training and validation stage HLS-SVM shows similar performance with HNN-EKF but better than HNN, whereas, in the testing stage, it shows three times better than HNN-EKF, hundred times better than HNN model.

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