In recent years,the researches on combination of quantum theory and neural networks have attracted much attention. This paper reviews the development and status about this field. Some quantum neural networks(QNN)model...In recent years,the researches on combination of quantum theory and neural networks have attracted much attention. This paper reviews the development and status about this field. Some quantum neural networks(QNN)models are discussed,the applications and prospects are also given,which show that QNN have great competence and potential in the computational intelligence field.展开更多
针对传统优化算法寻优精度低、收敛速度慢的问题,提出了基于量子理论的量子群搜索算法(Quantum Group Search Optimization,QGSO)。该算法主要采用了量子理论中的叠加态特性和概率表达特性,增强了种群的多样性,提高了群搜索算法(Group S...针对传统优化算法寻优精度低、收敛速度慢的问题,提出了基于量子理论的量子群搜索算法(Quantum Group Search Optimization,QGSO)。该算法主要采用了量子理论中的叠加态特性和概率表达特性,增强了种群的多样性,提高了群搜索算法(Group Search Optimization,GSO)的寻优精度;利用量子位直接编码和量子运算的高效计算能力大大提高了算法的优化效率,加快了收敛速度。在基准函数的试验测试中,对比其他2种量子进化算法,结果显示本文提出的算法在搜索精度和收敛速度上更具有优势。在实际应用中,以乙烯裂解炉的双烯质量收率为优化目标,确定最佳的操作条件变量,实验结果表明,双烯的收率得到明显提高并且迅速地找到了最佳的操作条件,为生产过程优化操作提供了理论支持,实现了裂解炉的优化控制。展开更多
文摘In recent years,the researches on combination of quantum theory and neural networks have attracted much attention. This paper reviews the development and status about this field. Some quantum neural networks(QNN)models are discussed,the applications and prospects are also given,which show that QNN have great competence and potential in the computational intelligence field.
