改进模糊c均值(FCM)和鸡群优化(CSO)的性能

2017 3rd International Conference on Science in Information Technology (ICSITech) Pub Date : 2017-10-01 DOI:10.1109/ICSITECH.2017.8257105

Suprihatin, I. R. Yanto, N. Irsalinda, Tuti Purwaningsih, Haviluddin, A. Wibawa

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引用次数: 8

摘要

模糊聚类的许多研究和相关应用仍然是有趣和重要的。为了改进基于UCI数据集的模糊聚类算法的局部最优性，本文对模糊c均值(FCM)和鸡群优化(CSO)算法进行了改进。在本研究中，本文提出的FCMCSO性能还与基于粒子群优化的FCM (FCMPSO)、基于人工蜂群的FCM (FCMABC)和基于FCM的FCM进行了比较。仿真结果表明，FCMCSO方法比其他三种方法具有更好的性能。

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A performance of modified fuzzy C-means (FCM) and chicken swarm optimization (CSO)

Numerous research and related applications of fuzzy clustering are still interesting and important. In this paper, modified Fuzzy C-Means (FCM) and Chicken Swarm Optimization (CSO) algorithm in order to improve local optima of Fuzzy Clustering presented by using UCI dataset. In this study, the proposed FCMCSO performance is also compared with three methods i.e. FCM based on Particle Swarm Optimization (FCMPSO), FCM based on Artificial Bee Colony (FCMABC), and also FCM. The simulation results indicated that the FCMCSO method have better performance than three other compared methods.

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2017 3rd International Conference on Science in Information Technology (ICSITech)

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