Artificial intelligence toolbox for planning and operation of power systems

2000 IEEE Power Engineering Society, Conference Proceedings

Volumn 2, Issue , 2000, Pages 1057-1062

  Wehenkel, L ^a   Mack, P ^a  

^a UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; ELECTRIC POWER SYSTEMS; INTELLIGENT SYSTEMS; NEURAL NETWORKS; TREES (MATHEMATICS);

ISOLATED POWER SYSTEM; NEAREST NEIGHBOR METHOD; OPERATION OF POWER SYSTEM; REGRESSION TREES;

MONTE CARLO METHODS;

EID: 0038440907     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PESW.2000.850085     Document Type: Conference Paper

References (8)

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3. L. Wehenkel, "Automatic learning techniques in power systems", Boston, Kluwer Academic, 1998.
4. V. Cherkassky and F. Mulier, "Learning from data. Concepts, Theory, and Methods", New York, Willey, 1998.
5. P. Geurts and L. Wehenkel, "Visualizing Dynamic Power System Scenarios for Data Mining", Proc. of LESCOPE'98, Large Engineering Syst. Conf. on Power Engineering, pp 217-224, Halifax, July 1998.
6. C. M. Bishop, "Neural Networks for Pattern Recognition", Oxford, Clarendon Press, 1995.
7. A. Muñoz, "Applicación de técnicas de redes neuronales artificiales al diagnóstico procesos industriales", PhD thesis, Universidad Pontificia de Comillas, Madrid, Spain, 1996.
8. P. Cholley, C. Lebrevelec, S. Vitet, and M. de Pasquale. A statistical approach to assess voltage stability limits. In Proc. of Bulk Power Syst. Dynamics and Contr. IV - Restructuring, Santorini, Greece, 1998.