Energy demand forecasting in Iranian metal industry using linear and nonlinear models based on evolutionary algorithms

Energy Conversion and Management

Volumn 58, Issue , 2012, Pages 1-9

  Piltan, Mehdi ^a   Shiri, Hiva ^a   Ghaderi, S F ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Energy demand; Evolutionary algorithm; Forecasting; Industrial sector

Indexed keywords

ARTIFICIAL INTELLIGENT; CONSUMPTION OF ENERGY; ECONOMIC DEVELOPMENT; ELECTRICITY TARIFF; ELECTRICITY-CONSUMPTION; ENERGY DEMAND FORECASTING; ENERGY DEMANDS; ENERGY FORECASTING; ERROR PERCENTAGE; FITNESS FUNCTIONS; FORECASTING MODELS; FUEL PRICES; INDUSTRIAL SECTOR; LONG TERM PLANNING; MEAN ABSOLUTE DEVIATIONS; METAL INDUSTRIES; NON-LINEAR MODEL; NONLINEAR FUNCTIONS; PREVIOUS YEAR; PSO ALGORITHMS; REAL NUMBER; REAL-CODED GENETIC ALGORITHM; ROOT MEAN SQUARE ERRORS; SOCIAL FUNCTION; SOCIAL WELFARE; SUSTAINABLE ENERGY SUPPLY; TURKISHS;

ARTIFICIAL INTELLIGENCE; ECONOMICS; ENERGY UTILIZATION; EVOLUTIONARY ALGORITHMS; FORECASTING; INDUSTRY; INVESTMENTS; METALLURGY; NONLINEAR SYSTEMS;

MEAN SQUARE ERROR;

EID: 84856285262     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2011.12.022     Document Type: Article

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