An ANN - PCA adaptive forecasting model
Iulian Năstac, Paul Dan Cristea · International Conference on Systems, Signals and Image Processing · 2012
The paper describes specific aspects that concern Principal Component Analysis (PCA) when using it as a preprocessing tool in a forecasting model. Principal component analysis is an efficient used statistical technique for dimensional reduction, and here we employ the PCA to decorrelate the input data before training a neural network architecture. This approach reveals important regularities in the PCA transformation matrix that can improve the entire model.