Integration of genetic algorithm, computer simulation and design of experiments for forecasting electrical energy consumption

This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on genetic algorithm (GA), computer simulation and design of experiments using stochastic procedures. First, time-series model is developed as a benchmark for GA and simulation. Computer simulatio...

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Bibliographic Details
Published in:	Energy policy Vol. 35; no. 10; pp. 5229 - 5241
Main Authors:	Azadeh, A., Tarverdian, S.
Format:	Journal Article
Language:	English
Published:	Oxford Elsevier Ltd 01.10.2007 Elsevier Elsevier Science Ltd
Series:	Energy Policy
Subjects:	Algorithms Applied sciences Computer simulation Computers Design Design of experiments Economic data Electric energy Electricity Electricity consumption Energy Energy consumption Energy economics Exact sciences and technology Experiments Forecasting Forecasts General, economic and professional studies Genetic algorithm Genetic algorithms Genetics Hypotheses Iran Methodology. Modelling Null hypothesis Simulation Stochastic models Studies Time series Treatment methods Variance analysis Iran Simulation Genetic algorithm Electricity consumption Experimental test Methodology Computer simulation Experimental design Time series Electric power consumption Forecasting Monthly variation
ISSN:	0301-4215, 1873-6777
Online Access:	Get full text
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