The nature of statistical learning theory
The nature of statistical learning theory
Multi-category classification by kernel based nonlinear subspace method
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Load Identification in Neural Networks for a Non-intrusive Monitoring of Industrial Electrical Loads
Computer Supported Cooperative Work in Design IV
Minimizing private data disclosures in the smart grid
Proceedings of the 2012 ACM conference on Computer and communications security
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A non-intrusive load monitoring system that estimates the behavior of individual electrical appliances from the measurement of the total household load demand curve is useful for the forecast of electric energydemand and better customer services. Furthermore, this system will become important for power companies to control peak electric energydemand in the near future. We have alreadyrep orted the system using Support Vector Machines (SVM) and SVM could establish sufficient accuracyfor the non-intrusive load monitoring system. However, SVM needs too much computational cost for training to establish sufficient accuracy. This paper shows Kernel based Subspace Classification can solve this problem with an equal accuracyof classification to SVM.