| 基于群体递增学习算法的癌症化学疗法优化技术研究 |
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| 引用本文： | 姜群,王越,宋文强.基于群体递增学习算法的癌症化学疗法优化技术研究[J].计算机应用,2007,27(3):721-723. |
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| 作者姓名： | 姜群 王越 宋文强 |
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| 作者单位： | 重庆工学院计算机科学与工程学院 重庆400050(姜群，王越)，第三军医大学基础医学部 重庆400050(宋文强) |
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| 摘 要： | 探索分布估计算法中最频繁用于解决现实生活中优化问题的基于群体递增学习算法在优化癌症化疗中的应用能力，并与遗传算法作相应比较。实验表明基于群体递增学习（PBIL）算法的搜寻速度以及搜寻到的可行解质量均优于遗传算法。
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| 关 键 词： | 化学疗法 基于群体递增学习算法 约束 优化 |
| 文章编号： | 1001-9081（2007）03-0721-03 |
| 收稿时间： | 2006-09-15 |
| 修稿时间： | 2006-09-14 |
An approach to optimize cancer chemotherapy using population based incremental learning algorithm |
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| JIANG Qun,WANG Yue,SONG Wen-qiang.An approach to optimize cancer chemotherapy using population based incremental learning algorithm[J].journal of Computer Applications,2007,27(3):721-723. |
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| Authors: | JIANG Qun WANG Yue SONG Wen-qiang |
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| Affiliation: | 1. College of Computer Science and Engineering, Chongqing Institute of Technology, Chongqing 400050, China; 2. Ministry of Fundamental Medical Science, Third Military Medical University, Chongqing 400050, China |
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| Abstract: | A methodology for using Estimation of Distribution Algorithm (EDA) to optimize cancer chemotherapy was proposed. The performance of population based incremental learning (PBIL) algorithm in optimizing cancer chemotherapy was studied. The experimental results show that PBIL algorithm outperforms genetic algorithms in both the speed of finding a feasible treatment schedule and the quality of the final solution. |
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| Keywords: | chemotherapy population based incremental learning algorithm constraint optimization |
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