Research Article

Application of Principal Component Analysis-Assisted Neural Networks for the Rotor Blade Load Prediction

Table 2

Correlation analysis of the process variables.


1.00
-0.461.00
0.42-0.401.00
-0.770.54-0.771.00
-0.710.550.900.931.00
-0.09-0.230.650.34-0.491.00
-0.500.120.25-0.130.080.691.00
-0.430.230.910.790.91-0.65-0.311.00
0.65-0.470.35-0.48-0.540.02-0.320.341.00
0.41-0.85-0.22-0.55-0.430.200.00-0.340.371.00
-0.25-0.33-0.33-0.660.130.340.490.210.00-0.051.00
0.49-0.530.49-0.520.67-0.45-0.190.440.79-0.500.011.00
-0.500.35-0.320.710.54-0.210.38-0.290.600.550.320.891.00
-0.61-0.57-0.990.70-0.62-0.21-0.340.45-0.780.49-0.21-0.900.931.00
-0.590.42-0.34-0.650.560.18-0.37-0.42-0.880.600.33-0.900.990.991.00
0.530.590.37-0.340.490.200.130.280.600.44-0.04-0.640.46-0.58-0.451.00
-0.510.48-0.50-0.30-0.38-0.450.250.210.29-0.580.30-0.040.640.54-0.530.53