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Multiple Quantum Spaces Based Genetic Coding Method

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  • Tao Gao

    (Department of Automation, North China Electric Power University, Baoding, China)

Abstract

Quantum genetic coding method plays an important role in improving the efficiency of optimization algorithm. The existing quantum genetic algorithm has some defects, that quantum encoding scheme is tend to reduce the stability, so that the algorithm is prone to premature convergence and falls into local minima. Therefore, the chain of multiple genes encoding scheme is used to extend in the multi-dimensional space for improving this algorithm. By function extremum and simulation of neural network weights optimization, according to the characteristics of qubits and the normalization condition, double and triple chain binding coding schemes are proposed. By experiments on multiple genes encoding scheme chain, the performance of the algorithm is tested. It shows that the algorithm can get better results by increasing the higher accuracy of solution chain genes. It is an effective strategy to improve the performance of genetic coding.

Suggested Citation

  • Tao Gao, 2014. "Multiple Quantum Spaces Based Genetic Coding Method," International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), IGI Global, vol. 6(2), pages 48-57, April.
    • Handle: RePEc:igg:japuc0:v:6:y:2014:i:2:p:48-57
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