Once being trained, FNN can forecast future loads right away.
一经训练，FNN就能预报未来负荷。
As one of FNN, RBF network is also widely used in many fields.
R BF神经网络作为多层前向神经网络的一种，同样有着广泛的应用。
The theory of fuzzy neural network (FNN) modeling for nonlinear systems is presented.
论述了模糊系统和神经网络相结合的非线性系统辨识理论。
The problem of rule explosion in FNN controller is solved for multi-variable systems.
采用自适应神经模糊推理系统，对控制器的参数进行优化。
A variable structure control method based on T-S fuzzy neural network (FNN) is brought forward.
提出基于T - S模糊神经网络的变结构控制方法。
Based on Fuzzy Neural Network (FNN), an intelligent adaptive sliding-mode guidance law is presented.
在自适应滑模导引律的基础上，提出了一种基于模糊神经网络(FNN)的自适应滑模导引律。
The Fuzzy Neural Network (FNN) methodology is proposed to realize the model of the nonlinear process.
模糊神经网络(FNN)方法可以实现非线性过程模型。
The new FNN is used in the control of hot rolling mill production and a satisfying result is obtained.
将这种模糊神经网络用于热轧产品的质量控制，获得了好的效果。
The experimental results of tape rectification have shown the effectiveness of the FNN predictive control.
带料纠偏试验结果已经证明了FNN预测控制的有效性。
This system, possesses the structure of neural net and learning algorithm, addressed as fuzzy neural net FNN.
该系统具有神经网络的结构和学习算法，称模糊神经网络FNN。
After the parameters of rule have been amended, the output of FNN can be well coincident with the data of loads.
规则参数经过修正后，FNN的输出能与负荷数据很好地吻合。
Gradient descent algorithm is an efficient method to train FNN, and it can be realized in batch or incremental manner.
梯度下降算法是训练多层前向神经网络的一种有效方法，该算法可以以增量或者批量两种学习方式实现。
In this paper, a new complex-valued blind equalization algorithm based on the feedforward neural network (N-FNN) is proposed.
提出了一种新的前馈神经网络(N - FNN)复值盲均衡算法。
On the basis of, some direct-control neurons are added to the FNN, and then a new FNN model is produced which is named as ZFNN.
在此基础上，结合列车运行安全控制的实际情况，加入直控神经元，构造了直控模糊神经网络控制（ZFNN）模型来保证控制系统符合故障-安全原则。
Then this paper attempts to optimize travel route using FNN because it has some similar physical properties with traffic network.
利用流体神经网络与道路交通网络具有相似性的特点，将流体神经网络技术引入交通网络的路线优化。
The structure of the FNN is given in the paper, which is the basic theory for the traffic pattern recognition and the elevator assignment.
针对控制目标对派梯原则进行详细的研究，并且派梯原则是以当前的交通模式为前提的，应用了交通模式识别的结果。
And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
In the research of reasoning machine, a FNN reasoning method is used to solve the problem of collision and inefficiency in the fuzzy rules reasoning.
在对推理机制的研究中，采用模糊神经网络推理方法解决了模糊规则推理时存在的冲突和低效率问题。
The process of submarine decision control is a representative fuzzy process. FNN can properly deal with fuzzy information and has consequence ability.
潜艇指挥决策控制过程是一个典型的模糊过程，模糊神经网络能够较好地处理模糊信息，并具备模糊推理能力。
The relation between the input of FNN, such as disturbance, system state parameters, and output of FNN, optimal rescheduling strategy, is built by FNN.
通过对模糊神经网络训练，建立干扰和半导体生产线状态等输入参数与优化的重调度策略输出之间的映射关系。
The rescheduling strategies are divided into line layer, machine group layer and machine layer. The samples for FNN are setup by simulation evaluation.
将重调度策略划分为半导体生产线、设备组和设备重调度层次，利用仿真评价确定优化的重调度策略，并获得样本数据。
This paper presents an integrated evaluation approach for concrete strength using Fuzzy Neural Networks (FNN) to take full advantage of the two methods.
为了充分利用这两种测强手段的特点，本文将模糊神经网络应用到混凝土强度综合评定中。
Moreover, given the influence of generation rate constraint (GRC) or alteration of parameters, the Fuzzy Neural Network (FNN) is used to control the ACE.
考虑到出力调节速率约束或系统参数改变对控制效果的影响，本文进一步采用模糊神经网络对系统加以控制。
This paper presents the studies of Fuzzy-Neural Network (FNN) control methods in the application of the full-bridge series type resonant DC-DC converter.
本论文研究的是模糊神经网络在全桥串联共振型DC - DC变换器控制中的应用。
The method can simplify the structure of network and reduce the time of training that supplies the possibility that FNN is used in realtime control system.
仿真结果表明该方法精简了网络的结构，减少了训练的时间，为模糊神经网络用于实时控制系统提供了可能的条件。
With FNN decompose technique added, the method has some merits of shorter training time, higher executing speed, higher reliability and anti noise abilities.
该网络适于进行多传感器刀具状态的识别和分类，具有训练时间短，执行速度快，可靠性高，抗噪能力强的特点。
FNN efficiently maps the complex non-linear relationship between data by drill and rebound methods for its automatic learning, generation and fuzzy logic inference.
由于模糊神经网络具有很强的自学习、泛化和模糊逻辑推理功能，它可以有效地映射出钻芯、回弹数据间复杂的非线性关系。
Compared with conventional fault diagnosis method, the FNN fault diagnosis method has better performance for single fault and its diagnosis result has higher precision.
与传统故障诊断方法相比，基于模糊神经网络的故障诊断方法对单一故障具有很好的识别能力，可以提高诊断精度。
The immune clone evolutionary(ICE) algorithm is presented to optimize the parameters of the fuzzy neural network(FNN) controller for the complex billet heating process.
针对复杂钢坯加热过程，提出了一种免疫克隆进化模糊神经网络（ICE-FNN）控制算法。首先根据现场样本数据建立过程神经网络模型；
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