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Electric supply and demand forecasting using seasonal grey model based on PSO-SVR
16 references·1 citing·39 second hop
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this work references cited by second hop

References

  • 1982Control problems of grey systems4,503 cited
  • 2012Grey system model with the fractional order accumulation622 cited
  • 2018A seasonal GM(1,1) model for forecasting the electricity consumption of the primary economic sectors280 cited
  • 2020A novel adaptive discrete grey model with time-varying parameters for long-term photovoltaic power generation forecasting218 cited
  • 2019A new multivariable grey prediction model with structure compatibility203 cited
  • 2015A novel fractional grey system model and its application180 cited
  • 2020Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion162 cited
  • 2017Grey forecasting method of quarterly hydropower production in China based on a data grouping approach148 cited
  • 2020An improved seasonal GM(1,1) model based on the HP filter for forecasting wind power generation in China127 cited
  • 2020Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors108 cited
  • 2019A novel hybrid multivariate nonlinear grey model for forecasting the traffic-related emissions100 cited
  • 2020Parameter optimization for nonlinear grey Bernoulli model on biomass energy consumption prediction86 cited
  • 2020Predicting monthly natural gas production in China using a novel grey seasonal model with particle swarm optimization83 cited

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  • 2020Grey–Lotka–Volterra model for the competition and cooperation between third-party online payment systems and online banking in China80 cited
  • 2014A Rolling Grey Model Optimized by Particle Swarm Optimization in Economic Prediction80 cited
  • 2012Optimization models based on GM (1,1) and seasonal fluctuation for electricity demand forecasting80 cited
  • Cited by

    • 2023Incentive strategies for low-carbon supply chains with information updating of customer preferences23 cited