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A genetic-algorithm-based remnant grey prediction model for energy demand forecasting
16 references·0 citing·31 second hop
A genetic-algorithm-based remnant grey prediction model for energy demand forecasting (2017)A genetic-algorithm-based remnant grey pr…Novel grey prediction model with nonlinear optimized time response method for forecasting of electricity consumption in China (2016)Novel grey prediction model w…Grey modelling based forecasting system for return flow of end-of-life vehicles (2016)Grey modelling based forecast…Electricity consumption prediction using a neural-network-based grey forecasting approach (2016)Electricity consumption predi…An improved grey multivariable model for predicting industrial energy consumption in China (2016)An improved grey multivariabl…A novel grey forecasting model and its optimization (2012)A novel grey forecasting mode…Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case (2011)Forecasting short-term electr…Forecasting energy consumption using a grey model improved by incorporating genetic programming (2010)Forecasting energy consumptio…Using genetic algorithms grey theory to forecast high technology industrial output (2007)Using genetic algorithms grey…ARIMA forecasting of primary energy demand by fuel in Turkey (2006)ARIMA forecasting of primary …Grey Information: Theory and Practical Applications (2005)Grey Information: Theory and …Application of grey model GM(1, 1) to vehicle fatality risk estimation (2004)Application of grey model GM(…Applying the Grey prediction model to the global integrated circuit industry (2003)Applying the Grey prediction …Applications of improved grey prediction model for power demand forecasting (2003)Applications of improved grey…Improved grey prediction models for the trans‐pacific air passenger market (1998)Improved grey prediction mode…Industrial and business forecasting methods (1982)Industrial and business forec…Control problems of grey systems (1982)Control problems of grey syst…China statistical yearbook (1988)Introduction to Grey system theory (1989)Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model (2012)Grey system model with the fractional order accumulation (2012)Using a novel multi-variable grey model to forecast the electricity consumption of Shandong Province in China (2018)Book Review: Time Series Analysis: Forecasting and Control (1977)Energy consumption and GDP: causality relationship in G-7 countries and emerging markets (2002)Time series forecasting using a hybrid ARIMA and neural network model (2003)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Modeling and forecasting of Turkey’s energy consumption using socio-economic and demographic variables (2010)Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Grey prediction with rolling mechanism for electricity demand forecasting of Turkey (2007)Discrete grey forecasting model and its optimization (2008)Forecasting the annual electricity consumption of Turkey using an optimized grey model (2014)The use of grey relational analysis in solving multiple attribute decision-making problems (2008)Integrating sustainability into supplier selection with grey system and rough set methodologies (2009)Multi-Criteria Decision Making (MCDM) Methods and Concepts (2023)A trigonometric grey prediction approach to forecasting electricity demand (2006)Fuzzy DEMATEL method for developing supplier selection criteria (2010)Application of a novel time-delayed polynomial grey model to predict the natural gas consumption in China (2017)A new multivariable grey prediction model with structure compatibility (2019)A novel conformable fractional non-homogeneous grey model for forecasting carbon dioxide emissions of BRICS countries (2019)On novel grey forecasting model based on non-homogeneous index sequence (2012)Forecasting Chinese CO2 emissions from fuel combustion using a novel grey multivariable model (2017)Application of the novel nonlinear grey Bernoulli model for forecasting unemployment rate (2006)New progress of Grey System Theory in the new millennium (2016)Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention (2002)Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil (2011)Using the R-MAPE index as a resistant measure of forecast accuracy (2013)
this work references cited by second hop

References

  • 1982Control problems of grey systems4,534 cited
  • 2005Grey Information: Theory and Practical Applications711 cited
  • 2006ARIMA forecasting of primary energy demand by fuel in Turkey626 cited
  • 1982Industrial and business forecasting methods515 cited
  • 2003Applications of improved grey prediction model for power demand forecasting387 cited
  • 2010Forecasting energy consumption using a grey model improved by incorporating genetic programming294 cited
  • 2003Applying the Grey prediction model to the global integrated circuit industry261 cited
  • 2004Application of grey model GM(1, 1) to vehicle fatality risk estimation222 cited
  • 2012A novel grey forecasting model and its optimization205 cited
  • 2011Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case192 cited
  • 2007Using genetic algorithms grey theory to forecast high technology industrial output169 cited
  • 2016Novel grey prediction model with nonlinear optimized time response method for forecasting of electricity consumption in China151 cited
  • 2016Electricity consumption prediction using a neural-network-based grey forecasting approach128 cited
  • 2016An improved grey multivariable model for predicting industrial energy consumption in China120 cited

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  • 1998Improved grey prediction models for the trans‐pacific air passenger market120 cited
  • 2016Grey modelling based forecasting system for return flow of end-of-life vehicles89 cited
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