A New Hybrid Fuzzy-Rough Dendritic Cell Immune Classifier

摘要：

　　The Dendritic Cell Algorithm (DCA) is an immune-inspired classification algorithm based on the behavior of natural dendritic cells (DC).This paper proposes a novel version of the DCA based on a two level hybrid fuzzy-rough model.In the top-level, the proposed algorithm,named RST-MFDCM, applies rough set theory to build a solid data pre processing phase.In the second level, RST-MFDCM applies fuzzy set theory to smooth the crisp separation between the DCs semi-mature and mature contexts.The experimental results show that RST-MFDCM succeeds in obtaining significantly improved classification accuracy.

关键词： Dendritic cell algorithm Rough sets Fuzzy sets Hybrid model

作者: Zeineb Chelly Zied Elouedi

作者单位: LARODEC, Institut Supérieur de Gestion de Tunis, Tunis, Tunisia

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 514-521

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）