Qubit Neural Tree Network With Applications in Nonlinear System Modeling

Abstract

This paper proposed a newly quantum-inspired Qubit neural tree network with improved Qubit neuron, cross-layer connections and distinct phase operation functions for each neurons. A hybrid evolutionary algorithm that combines the modified gene expression programming with particle swarm optimization is also introduced to obtain the optimal structure with related parameters of the Qubit neural tree network. Three nonlinear system modeling problems are selected to evaluate the effectiveness and performance of the proposed model. The simulation results indicate that the Qubit neural tree network has better nonlinear mapping and generalization ability than related methods do.