| 基于改进混合蛙跳算法的SVM分类算法 |
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| 引用本文： | 李希婷,孙璐,钱永亮,邹采荣. 基于改进混合蛙跳算法的SVM分类算法[J]. 电子工程师, 2011, 37(5): 41-44 |
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| 作者姓名： | 李希婷 孙璐 钱永亮 邹采荣 |
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| 作者单位： | 1. 东南大学信息科学与工程学院,南京,210096
2. 佛山科学技术学院信息科学与工程学院,佛山,528041 |
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| 基金项目： | 国家自然科学基金项目(No:60872073No:51075068); 广东省自然科学基金(10252800001000001)资助项目 |
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| 摘 要： | 支持向量机的训练需要求解一个带约束的二次规划问题，但在数据规模很大情况下，经典训练方法将变得很困难。本文提出一种基于改进的混合蛙跳算法的SVM训练算法。针对混合蛙跳算法搜索速度慢且容易陷入局部极值的缺陷，将模拟退火思想引入到混合蛙跳算法中，提出一种改进的混合蛙跳算法。该算法保持了混合蛙跳算法参数少和容易实现的特点，同时通过模拟退火的降温过程来提高算法的进化速度和精度。实验结果表明，该算法能显著提高收敛速度，并能有效克服局部极值，在SVM训练中具有良好效果。
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| 关 键 词： | 支持向量机 混合蛙跳算法 模拟退火 |
SVM Classification Algorithm Based on Improved Shuffled Frog Leaping Algorithm |
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| LI Xi-ting,SUN Lu,QIAN Yong-liang,ZOU Cai-rong. SVM Classification Algorithm Based on Improved Shuffled Frog Leaping Algorithm[J]. Electronic Engineer, 2011, 37(5): 41-44 |
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| Authors: | LI Xi-ting SUN Lu QIAN Yong-liang ZOU Cai-rong |
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| Affiliation: | LI Xi-ting1,SUN Lu1,QIAN Yong-liang1,ZOU Cai-rong2(1.School of Information Science and Engineering,Southeast University,Nanjing 210096,China,2.Foshan University,Foshan 528041,China) |
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| Abstract: | Since training SVM requires solving a restrained quadratic programming problem which becomes difficult for large datasets,a improved Shuffled Frog Leaping Algorithm(SFLA) is proposed as an alternative to current algorithm.In order to overcome the defects of SFLA such as slow searching speed in evolution and local minimum,an improved algorithm in which the mechanism of Simulated Annealing(SA) is involved into basic SFLA is put forward in this paper.The proposed algorithm is almost as simple as SFLA and impro... |
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| Keywords: | support vector machine(SVM) shuffled frog leaping algorithm(SFLA) simulated annealing(SA) |
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