首页 | 本学科首页   官方微博 | 高级检索  
     


A fuzzy clustering algorithm enhancing local model interpretability
Authors:J. L. Díez  J. L. Navarro  A. Sala
Affiliation:(1) Departamento de Ingeniería de Sistemas y Automática, Universidad Politécnica de Valencia, Camino de Vera, 14, 46022 Valencia, Spain
Abstract:In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.
Keywords:Fuzzy system identification  Fuzzy clustering  Interpretability  Local models
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号