| 直觉模糊最小二乘支持向量机 |
| |
| 引用本文： | 郭新辰,张超,李成龙. 直觉模糊最小二乘支持向量机[J]. 吉林大学学报(理学版), 2012, 50(5): 993-997 |
| |
| 作者姓名： | 郭新辰 张超 李成龙 |
| |
| 作者单位： | 东北电力大学 理学院, 吉林 吉林 132012 |
| |
| 基金项目： | 吉林省自然科学基金(批准号:201215165);符号计算与知识工程教育部重点实验室开放基金(批准号:93K-17-2010-K05);东北电力大学博士科研启动基金(批准号:BSJXM-200911) |
| |
| 摘 要： | 将直觉模糊集的相关理论引入到最小二乘支持向量机中, 建立了直觉模糊最小二乘支持向量机的数学模型, 并对模型的求解过程进行推导. 为验证该算法的有效性, 在人工数据集和标准数据集上进行仿真实验. 实验结果表明, 直觉模糊最小二乘支持向量机算法可降低分类时样本中噪声和野点对分类效果的影响.
|
| 关 键 词： | 直觉模糊； 最小二乘支持向量机； 分类 |
| 收稿时间： | 2012-05-21 |
Intuitionistic Fuzzy Least Square Support Vector Machine |
| |
| GUO Xin-chen,ZHANG Chao,LI Cheng-long. Intuitionistic Fuzzy Least Square Support Vector Machine[J]. Journal of Jilin University: Sci Ed, 2012, 50(5): 993-997 |
| |
| Authors: | GUO Xin-chen ZHANG Chao LI Cheng-long |
| |
| Affiliation: | College of Science, Northeast Dianli University, Jilin 132012, Jilin Province, China |
| |
| Abstract: | By means of the introduction of intuitionistic fuzzy set theory into the least squares support vector machine,the mathematical model of the intuitionistic fuzzy least squares support vector machine was established,and the solution to the model was derived.The simulation experiments were performed on both artificial data sets and benchmark data sets to verify the effectiveness of the proposed algorithm.The results show that the intuitionistic fuzzy least squares support vector machine algorithm can reduce the serious impact of sample noise and outliers on classification effect. |
| |
| Keywords: | intuitionistic fuzzy least squares support vector machine classification |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《吉林大学学报(理学版)》浏览原始摘要信息 |
|
点击此处可从《吉林大学学报(理学版)》下载全文 |
