| 双获胜节点SOM及其在TSP中的应用 |
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| 引用本文： | 韩旭明,李明,王丽敏.双获胜节点SOM及其在TSP中的应用[J].计算机工程与设计,2007,28(11):2637-2639. |
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| 作者姓名： | 韩旭明 李明 王丽敏 |
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| 作者单位： | [1]长春工业大学信息传播工程学院,吉林长春130012 [2]吉林大学计算机科学与技术学院,吉林长春130012 [3]长春税务学院计算机科学与技术系,吉林长春130117 |
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| 基金项目： | 国家自然科学基金
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吉林省社会科学基金
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长春税务学院院级基金 |
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| 摘 要： | 在Kohonen提出的SOM(self-organization map)神经网络的基础上,通过拓广SOM网络的获胜节点数量,引入惩罚修正因子,改进邻域和连接权函数等方法提出一种新的SOM即SOMDW(SOM with double-winner)模型.为了验证该模型的有效性,以旅行商问题(traveling salesman problem,TSP)为例对该模型进行检验,得到了满意的结果.另外为了增强SOMDW网络的动态聚类性能,提高解的精确性,还采用禁忌搜索的搜索方法.
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| 关 键 词： | SOM神经网络 双获胜节点 邻域函数 连接权函数 聚类 TSP问题 节点 应用 搜索方法 禁忌搜索 性能 动态聚类 增强 外为 结果 检验 salesman problem 旅行商问题 有效性 验证 模型 权函数 连接 邻域 改进 |
| 文章编号： | 1000-7024（2007）11-2637-03 |
| 修稿时间： | 2006-09-23 |
Double-winner SOM and Its application to TSP |
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| HAN Xu-ming,LI Ming,WANG Li-min.Double-winner SOM and Its application to TSP[J].Computer Engineering and Design,2007,28(11):2637-2639. |
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| Authors: | HAN Xu-ming LI Ming WANG Li-min |
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| Affiliation: | 1. College of Information and Spreading Engineering, Changchun University of Technology, Changchun 130012, China; 2. College of Computer Science and Technology, Jilin University, Changchun 130012, China; 3. Department of Computer Science and Technology, Changchun Taxation College, Changchun 130117, China |
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| Abstract: | Based on SOM(self-organization map)neural network developed by Kononen,a novel SOM model,namely SOMDW (SOM with double-winner)is proposed by increasing winner nodes and improving some functions such as neighbor function and con- nection weight function and introducing direction modifying factor in SOM network.In order to validate SOMDW model,an example of TSP(traveling salesman problem)is applied and some satisfying results are also obtained.In addition,in order to enhance the dynamic competition and clustering capability of SOMDW so that some accurate results is obtained by using SOM,tabu-search method is also applied. |
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| Keywords: | SOM neural network double-winner winner neighborhood function connection weight function clustering TSP problem |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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