Research Article

Forecasting CO2 Emissions in China’s Construction Industry Based on the Weighted Adaboost-ENN Model and Scenario Analysis

Table 4

The correlation coefficient matrix between 14 influencing factors.


CoalCokeGasolineKeroseneDieselFuel oilNatural gasElectricity

Coal1.000
Coke0.7481.000
Gasoline-0.835-0.8091.000
Kerosene0.4200.558-0.6211.000
Diesel0.5040.648-0.8450.4901.000
Fuel oil-0.562-0.4480.4850.023-0.6121.000
Natural gas0.1940.653-0.4840.4390.494-0.0741.000
Electricity-0.794-0.9010.757-0.573-0.6290.576-0.3831.000
0.8410.950-0.8250.5470.652-0.5480.477-0.9761.000
0.332-0.024-0.358-0.2080.394-0.488-0.233-0.0040.0851.000
0.7620.822-0.7220.2580.631-0.6760.313-0.8430.8840.3741.000
-0.667-0.6870.736-0.636-0.6680.452-0.2570.833-0.806-0.122-0.5821.000
-0.824-0.8280.909-0.671-0.7720.495-0.3620.907-0.918-0.211-0.7570.9311.000
-0.865-0.8570.914-0.636-0.7420.505-0.3710.922-0.944-0.224-0.8050.9010.9941.000

Note: indicates energy structure.