本文基于费用函数最小化方法，提出一种混合并行量子进化算法用于文本图像的边缘检测。

In this paper we present a hybrid parallel quantum evolutionary algorithm (PQEA) based on cost minimization technique for edge detection.

youdao

文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合，提出了两种混合量子进化算法。

Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid Quantum Evolutionary algorithms (QEA) based on combining QEA with Particle Swarm optimization (PSO).

youdao

此外，量子进化算法具有收敛快和好的全局搜索特性，因此它比传统的进化算法更适于并行结构的实现。

QEA is more suitable for parallel structure than the conventional evolutionary algorithms because of rapid convergence and good global search capability.

youdao

将量子群进化算法(QEA)与蚁群系统(acs)进行融合，提出一种新的量子蚁群算法(QACA)。

The algorithm is based on the combination of quantum evolutionary algorithm (QEA) and ant colony system (ACS), a new algorithm, quantum ant colony algorithm (QACA) is proposed.

youdao

该算法采用量子比特概率编码方式构造染色体，由量子旋转门操作实现种群进化。

This algorithm codes the chromosomes in the way of quantum bit probability, and makes the population evolve by the operation of quantum gate.

youdao

量子衍生进化算法是基于量子计算原理的一种进化算法。

Quantum Inspired Evolutionary Algorithm (QEA) is a type of evolutionary algorithm based on principles of Quantum Computing (QC).

youdao

通过直接将量子位的Bloch坐标视为基因位，提出一种基于量子位Bloch坐标的量子衍生进化算法。

By directly regarding the Bloch coordinates of qubit as genes in chromosome, a quantum-inspired evolution algorithm is proposed.

youdao

通过直接将量子位的Bloch坐标视为基因位，提出一种基于量子位Bloch坐标的量子衍生进化算法。

By directly regarding the Bloch coordinates of qubit as genes in chromosome, a quantum-inspired evolution algorithm is proposed.

youdao