A Multi-Coding GA-BP-RBF Model for China Human Capital Prediction

Human capital formation and accelerating economic growth is a representative complex system which is not suitable to measure and forecast by classic linear statistical approaches. This paper proposes a novel hybrid multi-coding GA-BP-RBF model for China human capital prediction. The hybrid model combines the multi-encoding genetic algorithm (MGA) and the back propagation (BP) algorithm to form a hybrid learning algorithm (MGA-BP) for training Radial Basis Function Networks (RBFNs). The human capital prediction results obtained are compared with existent bibliography, showing an improvement over the published methods.