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Examination and prediction of fog and haze pollution using a Multi-variable Grey Model based on interval number sequences
3 references·14 citing·40 second hop
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this work references cited by second hop

References

  • 1982Industrial and business forecasting methods515 cited
  • 2016Grey Data Analysis247 cited
  • 2012General grey numbers and their operations127 cited

Cited by

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  • 2020Forecasting manufacturing industrial natural gas consumption of China using a novel time-delayed fractional grey model with multiple fractional order58 cited
  • 2021Exploiting fractional accumulation and background value optimization in multivariate interval grey prediction model and its application55 cited
  • 2022A novel seasonal adaptive grey model with the data-restacking technique for monthly renewable energy consumption forecasting50 cited
  • 2023Accurate forecasts and comparative analysis of Chinese CO2 emissions using a superior time-delay grey model50 cited
  • 2023Forecasting China's hydropower generation using a novel seasonal optimized multivariate grey model49 cited
  • 2022A nonlinear interactive grey multivariable model based on dynamic compensation for forecasting the economy-energy-environment system39 cited
  • 2021A novel multivariate grey system model with conformable fractional derivative and its applications38 cited
  • 2023Interval time series forecasting: A systematic literature review34 cited
  • 2020On unified framework for discrete-time grey models: Extensions and applications

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34 cited
  • 2022Research and application of multi-variable grey optimization model with interactive effects in marine emerging industries prediction32 cited
  • 2021On unified framework for continuous-time grey models: An integral matching perspective32 cited
  • 2022A novel discrete multivariable grey model with spatial proximity effects for economic output forecast31 cited
  • 2020Parameter estimation for grey system models: A nonlinear least squares perspective31 cited