Forecasting model using rough sets and orthogonal wavelet networks
Qing‐Jie Kong · Systems engineering and electronics · 2005
Combining the orthogonal wavelet networks with rough sets theory, a forecasting model of the orthogonal wavelet networks based on rough rets is put forward. Using the principal component analysis (PCA) about input vectors, the model keeps away from the dimension avalanche of orthogonal wavelet networks. Combined the excellent characteristics of rough networks and orthogonal wavelet networks together, the model is provided with the favorable robust and function approximating ability. It especially fits to the precise forecasting applications with randomicity. The experiment results show that the model is superior to frame wavelet networks in some aspects of forecasting precision, network convergence and its robust to uncertain factors.