Dynamic filter weights neural network model integrated with differential evolution for day-ahead price forecasting in energy market

Expert Systems with Applications

Volumn 38, Issue 9, 2011, Pages 10974-10982

  Chakravarty, S ^a   Dash, P K ^b  

^a Regional College of Management   (India)

^b SIKSHA O ANUSANDHAN DEEMED TO BE UNIVERSITY   (India)

Author keywords

Differential evolution; Dynamic filter weights neuron; Energy market; Local linear wavelet neural network; Sliding mode control

Indexed keywords

ADALINE; ADAPTATION TECHNIQUES; ADAPTIVE WEIGHTS; ADJUSTABLE PARAMETERS; CALIFORNIA; CONVERGENCE PROPERTIES; DAY-AHEAD PRICES; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; DYNAMIC FILTER; ELECTRICITY PRICES; ENERGY MARKET; ENERGY MARKETS; EXPERIMENTAL DATA; FILTER WEIGHTS; FIRST ORDER; FORECASTING ELECTRICITY; FORECASTING PERFORMANCE; INVARIANCE CONDITION; LEAST SQUARE; LOCAL LINEAR; LOCAL LINEAR WAVELET NEURAL NETWORK; MEAN ABSOLUTE PERCENTAGE ERROR; NEURAL NETWORK MODEL; ROOT MEAN SQUARE ERRORS; SLIDING MODES; TIME VARYING LINEAR SYSTEMS; WAVELET NEURAL NETWORK MODEL; WAVELET NEURAL NETWORKS;

COMMERCE; DYNAMIC MODELS; EVOLUTIONARY ALGORITHMS; FORECASTING; LINEAR SYSTEMS; POWER QUALITY; SLIDING MODE CONTROL;

NEURAL NETWORKS;

EID: 79955606558     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.02.141     Document Type: Article

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