摘要
在一种进化聚类算法(ECM)的基础上提出了一种新的动态TSK模糊模型的建模算法,以往许多神经模糊模型都不适用于自适应在线学习,而文章模型能实时地调整模糊规则库及规则参数,具有较强的在线学习能力;仿真结果表明,该方法是有效的。
On the basis of a evolving clustering method （ECM）, a new modeling approach of dynamic TSK fuzzy model was proposed. In the past, several neuro-fuzzy models were not suitable for adaptive on--line learning, but the model proposed here can real--time adjust the fuzzy rule base and rule parameters, so it has powerful ability of on-line learning. The results of simulation demonstrate the effectiveness of the proposed modeling approaeh.
出处
《计算机测量与控制》
CSCD
2006年第4期528-529,共2页
Computer Measurement &Control
基金
湖南省自然科学基金(04JJY6036)。
