该文提出一种用于复杂的非线性未知系统辨识的混合神经网络模型—自适应模糊神经网络(AFNN)。
This paper presents a compound neural network model, i. e., adaptive fuzzy neural network (AFNN), which can be used for identifying the complicated nonlinear system.
与多元线性回归、模糊回归和自适应模糊神经网络相比，该模型学习精度高且具有较好的泛化能力，能取得较好的预测效果。
Comparing with the models based on multiple statistic analysis, generalized regress-ion neural network or adapted fuzzy neural network model, it shows better learning precision and generalization.
针对液压弯辊系统数学模型的非线性、时变特性，本文设计了一种模糊神经网络模型参考自适应控制器。
In view of the time-variable and nonlinear characteristics of mathematical model of hydraulic bending roll system, this thesis design a new nonlinear adaptive controler based on fuzzy neural network.
应用推荐