Quantum-inspired evolutionary algorithms: a survey and empirical study
Journal of Heuristics
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This paper proposes a structure that combines neural networks and quantum evolutionary algorithm, called a neural network with quantum evolutionary algorithm (NN-QEA), for the establishment of a nonlinear map when data are subject to outliers. Neural networks have the advantage of powerful modeling ability. Quantum evolutionary algorithm has the characteristics of rapid convergence and good global search capability. NN-QEA combines the advantages of both and realizes the goal of modeling and outliers rejection simultaneously. The effectiveness and the applicability of NN-QEA are demonstrated by experimental results on the modeling of the compressor characteristic map.