Combined use of unsupervised and supervised learning for daily peak load forecasting
- Author
- AMIN-NASERI, M. R1 ; SOROUSH, A. R1
[1] Department of Industrial Engineering, Tarbiat Modares University. Jalal Alahmad Highway. P.O. Box 14115-143, Tehran, Iran, Islamic Republic of - Source
Energy conversion and management. 2008, Vol 49, Num 6, pp 1302-1308, 7 p ; ref : 23 ref
- Publisher
- Elsevier, Oxford
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Artificial neural networks Clustering Feed forward neural networks Forecasting Peak load Self-organizing map
- Keyword (fr)
- Algorithme Analyse amas Analyse composante principale Autoorganisation Carte Consommation électricité Elément météorologique Evaluation performance Modèle hybride Modélisation Méthodologie Prévision Régime pointe Régression linéaire Réseau neuronal Temps météorologique
- Keyword (en)
- Algorithm Cluster analysis Principal component analysis Self organization Maps Electric power consumption Meteorological variable Performance evaluation Hybrid model Modeling Methodology Forecasting Peak load Linear regression Neural network Weather
- Keyword (es)
- Algoritmo Analisis cluster Análisis componente principal Autoorganización Mapa Consumo electricidad Elemento meteorológico Evaluación prestación Modelo híbrido Modelización Metodología Previsión Régimen punta Regresión lineal Red neuronal Tiempo meteorológico
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D06 Energy / 001D06A General, economic and professional studies / 001D06A01 Energy economics / 001D06A01A Methodology. Modelling
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D06 Energy / 001D06A General, economic and professional studies / 001D06A01 Energy economics / 001D06A01C Economic data / 001D06A01C4 Electric energy
- Discipline
- Energy
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 20337301
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.enconman.2008.01.016 
https://dx.doi.org/10.1016/j.enconman.2008.01.016
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