摘要
基于二叉树和模糊逻辑理论 ,提出了一种用于复杂系统建模的模糊树模型 .将线性模型和模糊集组织在树结构上 ,并给出了更新线性模型系数和模糊集隶属度函数的混合算法 .与其他建模方法相比 ,如 ANFIS,模糊树模型计算量小 ,精度高 ,尤其在高维数据建模中更为明显 .
Based on the binary tree structure and fuzzy logic theory,a fuzzy tree model applied to complex system modeling is proposed in this paper.Linear models and fuzzy sets are arranged in a tree structure.A hybrid training algorithm is used to update linear model coefficients and membership functions of the fuzzy sets.Compared with some other modeling methods,such as ANFIS,the proposed model is of less computation,higher accuracy,especially for high dimension data modeling.Simulation results demonstrate the advantages of this approach.
出处
《自动化学报》
EI
CSCD
北大核心
2000年第3期378-381,共4页
Acta Automatica Sinica
基金
国家自然科学基金
