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Forecasting natural gas demand in China: Logistic modelling analysis
5 references·10 citing·49 second hop
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References

  • 1994Comparing Predictive Accuracy5,578 cited
  • 2002Comparing Predictive Accuracy1,745 cited
  • 1998Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales836 cited
  • 2014How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?331 cited
  • 2011Forecasting natural gas consumption233 cited

Cited by

  • 2018A novel self-adapting intelligent grey model for forecasting China's natural-gas demand98 cited
  • 2025Machine learning natural gas price predictions94 cited
  • 2016Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods92 cited
  • 2018Estimates of energy consumption in China using a self-adaptive multi-verse optimizer-based support vector machine with rolling cross-validation84 cited
  • 2020A MFO-based conformable fractional nonhomogeneous grey Bernoulli model for natural gas production and consumption forecasting62 cited
  • 2019Forecasting annual natural gas consumption using socio-economic indicators for making future policies57 cited
  • 2016Research on China's energy supply and demand using an improved Grey-Markov chain model based on wavelet transform47 cited
  • 2018Combining Grey Model and Self-Adapting Intelligent Grey Model with Genetic Algorithm and Annual Share Changes in Natural Gas Demand Forecasting38 cited

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  • 2017Assessing the Quality of Natural Gas Consumption Forecasting: An Application to the Italian Residential Sector26 cited
  • 2021Application of a novel grey Bernoulli model to predict the global consumption of renewable energy25 cited