Extracting temporal patterns from time series data bases for prediction of electrical demand

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2972, Issue , 2004, Pages 21-29

  Rico, J Jesus ^a   Flores, Juan J ^a   Sotomane, Constantino ^b   Calderón, Félix ^a  

^a UNIVERSIDAD MICHOACANA DE SAN NICOLÁS DE HIDALGO   (Mexico)

^b EDUARDO MONDLANE UNIVERSITY   (Mozambique)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; DATA MINING; DATA REDUCTION; ELECTRIC INDUSTRY; ELECTRIC LOADS; ELECTRICITY; MATHEMATICAL MODELS; TIME SERIES ANALYSIS; ARTIFICIAL INTELLIGENCE; TIME SERIES;

ELECTRICAL DEMANDS; ELECTRICAL MARKETS; KNOWLEDGE DISCOVERY IN DATABASES (KDD) TECHNIQUES; TEMPORAL PATTERNS;

DATABASE SYSTEMS; FORECASTING;

APPROXIMATE PERIOD; ELECTRICAL DEMAND; KNOWLEDGE DISCOVERY IN DATA BASIS; MULTIPLE MODELS APPROACHES; MULTIPLE-MODELING; OPERATION REGIME; TEMPORAL PATTERN; TIME-SERIES DATA;

EID: 9444272234     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Ankerst, Mihael. Visual Data Mining, http://www.dissertation.de. 2000.
2. California ISO. http://www.caiso.com.
3. Cheeseman, Peter. AutoClass Documentation. 2000.
4. Montgomery, Douglas C.; Johnson, Lynwood; Gardiner, A.; S., John, Forecasting and Time Series Analysis, second edition. Mcgraw-Hill, Singapore, 1990.
5. Fayyad, Usama M.; Piatetsky-Shapiro, Gregory; Padhraic, Smyth; Ramasamy, Uthurusamy. Advances in Knowledge Discovery and Data Mining. AAAI Press/MIT press. 1996.
6. Garcia Villanueva, Moisés. Detección de Conglomerados en Espacios Métricos. Universidad Michoacana de San Nicolás de Hidalgo, Facultad de Ingeniería eléctrica. Morelia, México. 2001.
7. Geman, S.; Geman D. Stochastic Relaxation, Gibbs Distribution and the Bayesian Restoration of Images. IEEE Trans. on Pattern Analysis and Machine Intelligence. 6, 721-741, 1994.
8. Hamilton, Haward; Gurak, Ergun; Findlater, Leah; Olive, Wayne. Knowledge Discovery in Databases, http://www.cs.uregina.ca/~dbd/cs831.html.
9. Jahansen, T. A. Operation Regime Based Process Modeling and Identification. Department of Engineering cybernetics. The Norwegian Institute of Technology. University of Trondheim. Norway. 1994.
10. Johansen, T. A.; Murray-Smith, R., Multiple Model Approach to Modeling Control. Chapter 1. http://www.dcs.gla.ac.uk/~rod/Publications.htm. 1997.
11. Li, C.; Biswas, G. Unsupervised Learning with Mixed Numeric and Nominal Data. IEEE Transactions on Knowledge and Data Engineering. Vol. 14, No. 4, pages 676-690. 2002.
12. Mclachlan, Geoffrey J.; Krishnan, Thriyambakam. The EM Algorithm and Extensions. John Wiley & sons. Canada. 1997.
13. Perry, Chris, Short-Term Load Forecasting Using Multiple Regression Analysis. Rural Electric Power conference. 1999.
14. Shen, Wei-Min. Autonomous Learning from the Environment. WH Freeman and co. 1994.
15. Weron, R.; Kozlowska, B.; Nowicka-Zagrajek. Modeling Electricity Loads in California: a Continuous-Time Approach. Physica A 299, 344-350, www.elsevier.com/locate/physa, 2001.