Exploiting support vector clustering techniques for electrical load profiling
暂无分享,去创建一个
[1] S. Valero,et al. Development of a methodology for improving the effectiveness of customer response policies through electricity-price patterns , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.
[2] N.D. Hatziargyriou,et al. Two-Stage Pattern Recognition of Load Curves for Classification of Electricity Customers , 2007, IEEE Transactions on Power Systems.
[3] C. Senabre,et al. Methods for customer and demand response policies selection in new electricity markets , 2007 .
[4] C. Senabre,et al. Classification, Filtering, and Identification of Electrical Customer Load Patterns Through the Use of Self-Organizing Maps , 2006, IEEE Transactions on Power Systems.
[5] G. Chicco,et al. Comparisons among clustering techniques for electricity customer classification , 2006, IEEE Transactions on Power Systems.
[6] Z. Vale,et al. An electric energy consumer characterization framework based on data mining techniques , 2005, IEEE Transactions on Power Systems.
[7] F. Gubina,et al. Allocation of the load profiles to consumers using probabilistic neural networks , 2005, IEEE Transactions on Power Systems.
[8] Gianfranco Chicco,et al. Emergent electricity customer classification , 2005 .
[9] Thomas B. Smith,et al. Electricity theft: a comparative analysis , 2004 .
[10] José Edison Cabral,et al. Fraud detection in electrical energy consumers using rough sets , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).
[11] P. Postolache,et al. Load pattern-based classification of electricity customers , 2004, IEEE Transactions on Power Systems.
[12] J. Chiang,et al. A new kernel-based fuzzy clustering approach: support vector clustering with cell growing , 2003, IEEE Trans. Fuzzy Syst..
[13] Hava T. Siegelmann,et al. Support Vector Clustering , 2002, J. Mach. Learn. Res..
[14] Hava T. Siegelmann,et al. A support vector clustering method , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[15] C. S. Chen,et al. Synthesis of power system load profiles by class load study , 2000 .
[16] Robert P. W. Duin,et al. Support vector domain description , 1999, Pattern Recognit. Lett..
[17] Christopher J. C. Burges,et al. A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.
[18] C. S. Chen,et al. Application of load survey systems to proper tariff design , 1997 .
[19] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.
[20] R. Fletcher. Practical Methods of Optimization , 1988 .
[21] B. Pitt,et al. Application of Data Mining Techniques to Load Profiling , 2007 .
[22] Dan Apetrei,et al. Load pattern classification and profiling for a large supply company , 2007 .
[23] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[24] T. Caliński,et al. A dendrite method for cluster analysis , 1974 .
[25] S. Sinha. A Duality Theorem for Nonlinear Programming , 1966 .