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Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey
2 references·4 citing·26 second hop
Application of genetic algorithm (GA) technique on demand estimation of fossil fuels in Turkey (2008)Application of genetic algorithm (GA) tec…A real options evaluation model for the diffusion prospects of new renewable power generation technologies (2006)A real options evaluation mod…Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach (2003)Estimating energy demand of T…A comparative study on prediction methods for China's medium- and long-term coal demand (2015)A comparative study on predic…China’s primary energy demands in 2020: Predictions from an MPSO–RBF estimation model (2012)China’s primary energy demand…Using Bees Algorithm and Artificial Neural Network to Forecast World Carbon Dioxide Emission (2011)Using Bees Algorithm and Arti…Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm) (2011)Forecasting future oil demand…ARIMA forecasting of primary energy demand by fuel in Turkey (2006)Grey prediction with rolling mechanism for electricity demand forecasting of Turkey (2007)Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India (2010)Interval Grey Prediction Models with Forecast Combination for Energy Demand Forecasting (2020)Learning Curves in Manufacturing (1990)Investment under Uncertainty (1994)Investment Under Uncertainty. (1994)The use of real options approach in energy sector investments (2011)Overcoming barriers and uncertainties in the adoption of residential solar PV (2015)A real options model for renewable energy investment with application to solar photovoltaic power generation in China (2016)MONEY, INCOME, AND CAUSALITY (1972)ON THE RELATIONSHIP BETWEEN ENERGY AND GNP (1978)Energy demand estimation of South Korea using artificial neural network (2009)Energy consumption modeling using artificial neural networks: The case of the world’s highest consumers (2016)Estimation and control of Spanish energy-related CO2 emissions: an input–output approach (2002)Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran (2010)Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA (2017)Prediction of carbon dioxide emissions based on principal component analysis with regularized extreme learning machine: The case of China (2017)Forecasting Nitrous Oxide emissions based on grey system models (2019)Ant colony optimization approach to estimate energy demand of Turkey (2007)An oil imports dependence forecasting system based on fuzzy time series and multi-objective optimization algorithm: Case for China (2022)Energy consumption in China: past trends and future directions (2004)What induced China's energy intensity to fluctuate: 1997–2006? (2007)Input-output analysis foundations and extensions (2009)Energy-related CO2 emission peaking target and pathways for China's city: A case study of Baoding City (2019)Economic and intensity effects of coal consumption in China (2021)
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References

  • 2006A real options evaluation model for the diffusion prospects of new renewable power generation technologies273 cited
  • 2003Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach205 cited

Cited by

  • 2011Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm)77 cited
  • 2011Using Bees Algorithm and Artificial Neural Network to Forecast World Carbon Dioxide Emission67 cited
  • 2012China’s primary energy demands in 2020: Predictions from an MPSO–RBF estimation model58 cited
  • 2015A comparative study on prediction methods for China's medium- and long-term coal demand37 cited

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