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Assessing the Quality of Natural Gas Consumption Forecasting: An Application to the Italian Residential Sector
6 references·0 citing·28 second hop
Assessing the Quality of Natural Gas Consumption Forecasting: An Application to the Italian Residential Sector (2017)Assessing the Quality of Natural Gas Cons…Forecasting China’s natural gas demand based on optimised nonlinear grey models (2017)Forecasting China’s natural g…Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods (2016)Year Ahead Demand Forecast of…Forecasting natural gas demand in China: Logistic modelling analysis (2015)Forecasting natural gas deman…Linear Regression Models to Forecast Electricity Consumption in Italy (2012)Linear Regression Models to F…Forecasting natural gas consumption (2011)Forecasting natural gas consu…A time varying parameter approach to the Chinese aggregate consumption function (1996)A time varying parameter appr…Pooling Cross Section and Time Series Data in the Estimation of a Dynamic Model: The Demand for Natural Gas (1966)Forecasting with artificial neural networks: (1998)Temporal and spatial trends of residential energy consumption and air pollutant emissions in China (2013)A novel self-adapting intelligent grey model for forecasting China's natural-gas demand (2018)Econometric policy evaluation: A critique (1976)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Determinants of household saving in China (2006)Market reforms and consumption puzzles in China (2008)Evaluating the Financial Performance of Timberland Investments in the United States (2010)Economic variables and electricity consumption in Northern Cyprus (2001)Forecasting electricity consumption in New Zealand using economic and demographic variables (2004)Electricity consumption forecasting in Italy using linear regression models (2009)Electricity consumption forecasting for Turkey with nonhomogeneous discrete grey model (2017)Comparing Predictive Accuracy (1994)Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales (1998)Comparing Predictive Accuracy (2002)Machine learning natural gas price predictions (2025)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)Time series forecasting using a hybrid ARIMA and neural network model (2003)Comparison of Forecasting India’s Energy Demand Using an MGM, ARIMA Model, MGM-ARIMA Model, and BP Neural Network Model (2018)Industry 4.0 and demand forecasting of the energy supply chain: A literature review (2021)Multimodal Data Guided Spatial Feature Fusion and Grouping Strategy for E-Commerce Commodity Demand Forecasting (2021)Introduction to Grey system theory (1989)A hybrid model based on selective ensemble for energy consumption forecasting in China (2018)Forecasting U.S. shale gas monthly production using a hybrid ARIMA and metabolic nonlinear grey model (2018)Can expanding natural gas consumption reduce China's CO2 emissions? (2019)
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References

  • 2011Forecasting natural gas consumption233 cited
  • 2017Forecasting China’s natural gas demand based on optimised nonlinear grey models161 cited
  • 2015Forecasting natural gas demand in China: Logistic modelling analysis107 cited
  • 2012Linear Regression Models to Forecast Electricity Consumption in Italy98 cited
  • 2016Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods92 cited
  • 1996A time varying parameter approach to the Chinese aggregate consumption function24 cited

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