| 求解聚类问题的改进人工鱼群算法 |
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| 引用本文： | 王会颖,章义刚.求解聚类问题的改进人工鱼群算法[J].微机发展,2010(3):84-87,91. |
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| 作者姓名： | 王会颖 章义刚 |
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| 作者单位： | 安徽财贸职业学院计算机系;合肥学院; |
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| 基金项目： | 安徽省自然科学基金项目(KJ2008B021) |
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| 摘 要： | 聚类在数据挖掘、统计学、机器学习等很多领域都有很大应用。聚类问题可以归结为一个优化问题。人工鱼群算法（AFSA）是一种新提出的新型仿生优化算法。在分析AFSA存在不足的基础上，提出一种改进人工鱼群算法，并应用于求解聚类问题。算法保持了AFSA算法简单、易实现的特点．通过改进个体鱼的行为，并引入均匀交叉算子，将人工鱼群算法和遗传算法融合，显著提高了算法运行效率和求解质量。仿真实验取得了较好的结果。
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| 关 键 词： | 聚类 人工鱼群算法 交叉算子 优化 |
An Improved Artificial Fish-Swarm Algorithm of Solving Clustering Analysis Problem |
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| WANG Hui-ying,ZHANG Yi-gang.An Improved Artificial Fish-Swarm Algorithm of Solving Clustering Analysis Problem[J].Microcomputer Development,2010(3):84-87,91. |
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| Authors: | WANG Hui-ying ZHANG Yi-gang |
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| Affiliation: | WANG Hui-ying1,ZHANG Yi-gang2(1.Department of Computer Science,Anhui Finance & Trade Vocational College,Hefei 230061,China,2.Hefei University,Hefei 230022,China) |
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| Abstract: | Clustering has its roots in many areas,including data mining,statistics,and machine learning and can be regarded as an optimization problem.Artificial fish swarm algorithm(AFSA) is a novel bio-inspired optimizing method.After analyzing the disadvantages of AFSA,presents an improved artificial fish swarm optimization algorithm of solving clustering analysis problem.By improving the artificial fish's behaviors and combining artificial fish-swarm algorithm with genetic algorithm,the algorithm is as simple for ... |
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| Keywords: | clustering artificial fish swarm algorithm crossover operator optimization |
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