Qubit Neural Tree Network With Applications in Nonlinear System Modeling | Zendy

Feng Qi | Zendy; Chao Chen | Zendy

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Qubit Neural Tree Network With Applications in Nonlinear System Modeling

Author(s) -

Feng Qi,

Chao Chen

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2869894

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

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.

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