| 基于改进量子遗传算法的过程神经元网络训练 |
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| 引用本文： | 李欣,程春田,曾筠.基于改进量子遗传算法的过程神经元网络训练[J].控制与决策,2009,24(3). |
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| 作者姓名： | 李欣 程春田 曾筠 |
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| 作者单位： | 1. 大连理工大学,电子与信息工程学院,辽宁,大连,116024;大庆石油学院,计算机与信息技术学院,黑龙江,大庆,163318
2. 大连理工大学,水电与水信息研究所,辽宁,大连,116024 |
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| 摘 要： | 针对过程神经元网络由于模型参数较多BP算法不易收敛的问题,提出一种基于量子位Bloch坐标的量子遗传算法.将该算法融合于过程神经网络的训练.按权值参数的个数确定量子染色体上的基因数并完成种群编码,通过新的量子旋转门完成个体的更新.算法中的每条染色体携带3条基因链,因此可扩展对解空间的遍历性,加速优化进程.以两组二维三角函数的模式分类问题为例,仿真结果表明该方法不仅收敛速度快,而且寻优能力强.
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| 关 键 词： | 过程神经元网络 量子遗传算法 学习算法 |
| 收稿时间： | 2008-1-30 |
| 修稿时间： | 2008-4-25 |
Training of process neural networks based on improved quantum genetic algorithm |
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| LI Xin,CHENG Chun-tian,ZENG Yun.Training of process neural networks based on improved quantum genetic algorithm[J].Control and Decision,2009,24(3). |
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| Authors: | LI Xin CHENG Chun-tian ZENG Yun |
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| Affiliation: | 1a.School of Electronics and Information Engineering;1b.Institute of Hydropower System and Hydroinformatics;Dalian University of Technology;Dalian 116024;China;2.School of Computer and Information Technology;Daqing Petroleum Institute;Daqing 163318;China. |
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| Abstract: | Aiming at the problem that it is difficult for BP algorithm to converge because of more parameters in training of process neural networks based on orthogonal basis expansion,a solution on the basis of an improved quantum genetic algorithm is proposed in the paper.An improved quantum genetic algorithm based on Bloch coordinates of qubits is proposed,which is integrated into the training of process neural networks.The number of genes on a chromosome is determined by the number of weight parameters and populat... |
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| Keywords: | Process neural networks Quantum genetic algorithm Learning algorithm |
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