在本文中，我们提出了一个真正的水泥回转窑的非线性预测和仿真模型，利用非线性识别技术的局部线性神经的模糊（LLNF）的模型。对于第一次提出，仿真模型，以及与一个精确的水泥回转窑的预测15分钟地平线的预测因子1。
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针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性，提出了一种基于最优预测的神经元模糊自整定PID控制算法。
To the widely existed characteristics of time-delay, non-linear and timevarying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
基于模糊神经网络算法研究了非线性系统的噪声消除问题，设计了一类非线性自适应逆噪声消除控制器。
Based on Fuzzy Neural Network, the noise canceling problem of the nonlinear system was studied. A type of nonlinear adaptive noise controller was proposed.
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.
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