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Forecasting natural gas demand in China: Logistic modelling analysis · Study

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ArticleForecasting natural gas demand in China: Logistic modelling analysis

Faheemullah Shaikh2015

Article2015

Forecasting natural gas demand in China: Logistic modelling analysis

Faheemullah Shaikh · Qiang Ji

107 citations·0/0 files stored·International Journal of Electrical Power & Energy Systems

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Forecasting Techniques and Applications Energy, Environment, Economic Growth Energy Load and Power Forecasting

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References

1994Comparing Predictive Accuracy 2002Comparing Predictive Accuracy 1998Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales 2014How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?2011Forecasting natural gas consumption

Cited by

2018A novel self-adapting intelligent grey model for forecasting China's natural-gas demand 2025Machine learning natural gas price predictions 2016Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods 2018Estimates of energy consumption in China using a self-adaptive multi-verse optimizer-based support vector machine with rolling cross-validation 2020A MFO-based conformable fractional nonhomogeneous grey Bernoulli model for natural gas production and consumption forecasting 2019Forecasting annual natural gas consumption using socio-economic indicators for making future policies 2016Research on China's energy supply and demand using an improved Grey-Markov chain model based on wavelet transform 2018

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Details

Year2015

Typearticle

Published2015-11-28

VenueInternational Journal of Electrical Power & Energy Systems

ISSN-L0142-0615

Languageen

Citations107

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1016/j.ijepes.2015.11.013

openalex_workW2182392273

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Combining Grey Model and Self-Adapting Intelligent Grey Model with Genetic Algorithm and Annual Share Changes in Natural Gas Demand Forecasting