A Hybrid Model Equipped with the Minimum Cycle Decomposition Concept for Short-Term Forecasting of Electrical Load Time Series

Electricity load forecasting is an essential, however complicated work. Due to the influence of a large number of uncertain factors, it shows complicated nonlinear combination features. Therefore, it is difficult to improve the prediction accuracy and the tremendous breadth of applicability especial...

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Veröffentlicht in:	Neural processing letters 2017-12, Vol.46 (3), p.1059-1081
Hauptverfasser:	He, Zhaoshuang, Li, Caihong, Shen, Yulin, He, Anping
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial Intelligence Artificial neural networks Back propagation networks Complex Systems Computational Intelligence Computer Science Decomposition Electrical loads Electricity Energy consumption Evolutionary computation Forecasting Genetic algorithms Mathematical models Methods Model accuracy Neural networks Optimization Particle swarm optimization Performance enhancement Prediction models Resultants Stochastic models Support vector machines System theory Time series Wavelet transforms
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