Structure and parameters optimization of fuzzy rough neural network
Yuling Ye · Systems engineering and electronics · 2009
A kind of fuzzy rough neural network(FRNN) with five layers is proposed based on fuzzy rough membership functions.A switch function is used to describe the link among neurons,thus both the optimization of structure and parameters learning are transformed to a pure function optimization problem.A hybrid intelligent optimization algorithm(HIOA) is proposed to optimize the structure and parameters of FRNN and the fitness function considers both accuracy of the model and succinctness of FRNN simultaneousy.The typical experiment results show that FRNN is suitable for modeling nonlinear systems and it is better than the traditional neural network and its optimization method on both accuracy and generalization.