An enhanced Kernel Fuzzy C-Means Algorithm based on bio-inspired computing methods | |
Liu Y(刘洋); Hu KY(胡琨元)![]() ![]() | |
作者部门 | 信息服务与智能控制技术研究室 |
会议名称 | International Conference on Electronics, Information Technology and Intellectualization, EITI 2014 |
会议日期 | August 16-17, 2014 |
会议地点 | Shenzhen, China |
会议录名称 | Electronics, Information Technology and Intellectualization - International Conference on Electronics, Information Technology and Intellectualization, EITI 2014 |
出版者 | Taylor & Francis Group |
出版地 | London |
2014 | |
页码 | 115-118 |
收录类别 | EI |
EI收录号 | 20153501217505 |
产权排序 | 1 |
ISBN号 | 978-1-138-02741-1 |
关键词 | Data Clustering Bio-inspired Computing Optimization Algorithm Kernel Fuzzy C-means Algorithm Artificial Bee Colony |
摘要 | In data analysis and data mining technique fields, one of the most widely used methods is clustering. Recently, one of the bio-inspired computing optimization algorithms called the Artificial Bee Colony (ABC) algorithm has been introduced, which has many characteristics, such as simple, robust, stochastic global optimization. In this paper, an enhancedKernel Fuzzy C-MeansAlgorithm (KFCM) based on theABC algorithm for data clustering is proposed. Compared with other popular bio-inspired computing optimization algorithms in data clustering, the results proved that the number of iterations is fewer, the convergence speed is faster and there is also a large improvement in the quality of clustering. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.sia.cn/handle/173321/20081 |
专题 | 信息服务与智能控制技术研究室 |
作者单位 | Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
推荐引用方式 GB/T 7714 | Liu Y,Hu KY,Zhu YL,et al. An enhanced Kernel Fuzzy C-Means Algorithm based on bio-inspired computing methods[C]. London:Taylor & Francis Group,2014:115-118. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
An enhanced Kernel F(2371KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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