1) fuzzy recurrent neural network
模糊递归神经网络
1.
A multi-objective optimization based dynamic fuzzy recurrent neural network(FRNN)modeling method was designed to control the pH neutralization process by generalized predictive controller(GPC).
设计了一种基于多目标的动态模糊递归神经网络(FRNN)建模方法,用于pH中和过程的广义预测控制。
2.
The model dynamically sets the target temperature at the surface of slabs with support vector machine,forecasts the surface temperature of slabs with diagonal recurrent neural network,and dynamically controls and distributes the water flow of secondary cooling with T-S fuzzy recurrent neural network.
该模型采用支持向量机(SVM)实现板坯表面目标温度的动态设定,采用对角递归神经网络(DRNN)实现板坯表面温度的预测,采用T-S模糊递归神经网络实现二次冷却水动态调整与分配。
2) Recurrent fuzzy neural network
递归模糊神经网络
1.
Recurrent Fuzzy Neural Network Variable Structure Position Controller Based on Vector Control of PMLSM;
采用递归模糊神经网络的永磁直线同步电机变结构控制
2.
A kind of recurrent fuzzy neural network(RFNN) is constructed,in which,recurrent neural network is used to realize fuzzy inference and temporal relations are embedded in the network by adding feedback connections on the first layer of the network.
构造了一种递归模糊神经网络(RFNN),该RFNN利用递归神经网络实现模糊推理,并通过在网络的第一层添加了反馈连接,使网络具有了动态信息处理能力。
3.
A variable-structure control of a permanent magnet linear synchronous motor(PMLSM) servo-drive system using a recurrent fuzzy neural network was put forward to solve the problem of poor control precision in the servo system of packaging binding machine.
根据裹包机的驱动系统控制精度较差的问题,提出采用应用递归模糊神经网络变结构控制线性同步电动机伺服系统,经过仿真,结果表明,该控制系统克服了上述缺点。
3) recurrent compensatory fuzzy-neuro network
递归补偿模糊神经网络
4) recursion T-S fuzzy neural network
递归T-S模糊神经网络
5) dynamic recurrent fuzzy neural network
动态递归模糊神经网络
1.
A novel dynamic recurrent fuzzy neural network is presented in this paper, and its dynamic back propagation algorithm is formulated according its mathematic models.
提出了一种新型的动态递归模糊神经网络,并根据动态递归神经网络的数学模型推导出其动态反向传播学习算法,仿真结果表明对于动态系统的辨识,动态递归模糊神经网络较传统模糊神经网络在辨识精度和稳定性方面具有更好的效果。
6) TSK-type recurrent fuzzy neural network
TSK型递归模糊神经网络
1.
It uses TSK-type recurrent fuzzy neural network.
该方法中使用了一种TSK型递归模糊神经网络,可同时动态在线进行结构学习和参数学习,以提高位置控制静态精度和动态跟踪性能,仿真结果表明,所设计的TSK型模糊神经网络位置控制器响应速度快,跟踪性能好,输出精度高,动、静态特性优于传统PID。
补充资料：模糊
1.亦作"模胡"。 2.不分明;不清楚。 3.谓草率，马虎。 4.混淆。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条