Energy consumption is closely related to industrial structure, economic prosperity, and
population. Because of the Granger causal relationship between GDP and energy …

In predicting energy consumption, classic econometric and statistical models are used to
forecast energy consumption. These models may have limitations in an increasingly fast …

Forecasting energy demand in emerging nations is a critical policy tool utilized by decision
makers worldwide. However, as estimated economic and demographic characteristics …

Existing macroeconomic forecasting methods primarily focus on the characteristics of
economic data, but they overlook the energy-related features concealed behind these …

Modern computing resources, including machine learning-based techniques, are used to
maintain stability between the demand and supply of electricity. Machine learning is widely …

Many engineers and scientists concern with future energy demand. They use many different
statistical methods to estimate future energy demand such as multiple linear regression …

Accurately predicting energy consumption (EC) is a difficult task, owing to its inherent
complexity and nonlinearity features. To decrease the complexity of EC predictions, applying …

The prediction of energy consumption is of great significance to the stability of the regional
energy supply. In previous research on energy consumption forecasting, researchers have …

In order to analyze the factors that affect energy consumption in Hunan Province
comprehensively, firstly, this paper used the Logarithmic Mean Divisia Index (LMDI) and …

The energy price influence system is one of the key mechanisms in the study of energy
consumption. China's household energy consumption has obvious regional differences, and …