An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting result...An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization,and technological progress as the input variables. On the basis of historical annual data from1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.展开更多
According to Chinese national auto standard GB3730.1 - 88, cars are classified as 5 grades by engine displacement, i.e. mini car, subcom-pact car, compact car, intermediate car and limousine.
文摘An improved energy demand forecasting model is built based on the autoregressive distributed lag(ARDL) bounds testing approach and an adaptive genetic algorithm(AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization,and technological progress as the input variables. On the basis of historical annual data from1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively.
文摘According to Chinese national auto standard GB3730.1 - 88, cars are classified as 5 grades by engine displacement, i.e. mini car, subcom-pact car, compact car, intermediate car and limousine.
