理解神经网络的第一步是从对抽象生物神经开始，并把重点放在阈值逻辑单元（TLU）这一特征上。
The first step toward understanding neural nets is to abstract from the biological neuron, and to focus on its character as a threshold logic unit (TLU).
提出了利用模糊逻辑-神经网络分析高压电气设备绝缘参数变化趋势的方法。
The fuzzy logic-neural network is used to analyze the tendency of insulation parameter change of HV(High Voltage) electric equipment.
这样设置便可以创建不包含隐藏层的神经网络模型，从而使该神经网络模型与逻辑回归等效。
This setting will create a neural network model that does not contain a hidden layer, and that therefore is equivalent to logistic regression.
模糊认知图作为一种模糊逻辑和神经网络相结合的产物，为复杂系统建模提供了一种有效工具。
Fuzzy cognitive maps as a soft computing method, which combines the synergistic fuzzy logic and theories of neural networks provides a powerful tool for the complex system modeling.
模拟结果表明利用该算法训练的模糊层次神经网络具有较好的非逻辑归纳能力和特征抽取能力，并且学习速度也大大加快。
The simulation result is that the Fuzzy forward neural networks which is trained by this algorithm have good non-logic generalization and feature extraction ability, as well as fast learning speed.
由于它们在特性上有许多共同性和互补性，将遗传算法、神经网络与模糊逻辑相结合的研究已成为当前的研究热点之一。
The research on combinations of genetic algorithms, neural network and fuzzy logic is attracting the attention of many researchers because of many common and complementary features among them.
近年来，由于神经网络、模糊逻辑等智能信息处理技术的兴起，电路与器件的建模也开始使用这类方法。
In recent years, because of the emergence of intelligent information processing technology, such as neural networks and fuzzy logic, circuit and device modeling have begun to use such methods.
介绍一种用循环多层感知器神经网络实现符号逻辑推理系统的方法。
A method of implementing symbol logic inference system using recurrent multilayer perceptron neural networks is presented in this paper.
因此，基于神经网络、模糊逻辑等智能计算的板形测控方法已经成为研究的热点。
So the research on intelligent methods which are based on neural network and fuzzy logic have become a focus today.
为解决汽车安全气囊适时、正确触发问题，将模糊逻辑与人工神经网络技术引入汽车安全气囊触发控制算法研究。
The fuzzy logic and artificial neural network technologies are introduced into the algorithm for airbag deployment control, with a view to the appropriate and correct deployment of the airbag.
采用神经网络与模糊逻辑相结合的方式，构造了一种自适应pid控制器。
An adaptive PID controller is designed by combining neutral network with fuzzy logic.
该系统由图像捕获单元，3个并行工作的神经网络识别单元、运动特征计算单元、融合逻辑和相应的软件构成。
This system is made up of image capture unit, 3 parallel neural network recognition units, mobile characteristics calculation unit, syncretism logic, and corresponding software.
多年来，人们一直致力于模糊逻辑和神经网络结合方面的研究，并且收到了很好的效果，尤其在工业过程建模和控制方面。
People have studied the combination of fuzzy logic and neural network. For many years, and achieved good results, especially in the hand of industry process modeling and control.
实验表明，智能神经网络系统组成原理将面向对象、符号逻辑融于神经网络中，提供了构造功能完备的智能系统的途径。
The experiment shows that with merging the Object Oriented concept and symbol logic, the Intelligent Neural Network system Theory provides a way to build a big, complex NN system.
采用模糊逻辑和神经元网络控制策略，设计了新的控制算法来解决阀控马达控制问题。
By using the control strategies of fuzzy logic and neural networks, a new control algorithm was designed to solve the control problems.
基于模糊逻辑理论和人工神经元网络，提出了将模糊神经网络应用于变压器故障诊断的方法。
Based on fuzzy logic theory and artificial neural networks, the method of the transformer fault diagnosis with fuzzy neural networks is presented.
ANFIS设计方法是一种将模糊逻辑系统(FLS)和人工神经网络系统(ann)相结合，利用两者各自的优点所形成的混合智能系统。
The ANFIS design method is a blend intelligent system which combines the Fuzzy Logic system (FLS) and the Annual Neural Network (ANN) and USES their's strongpoints.
讨论了模糊逻辑和神经网络控制器在电液伺服位置系统中的应用。
Fuzzy logic and neural network controller and their applications in an electro hydraulic servo position system are discussed.
本文的研究内容是基于模糊逻辑和人工神经网络的智能控制策略及其在运动控制中的应用。
This thesis focuses on the intelligent control strategies based on fuzzy logic and neural networks and its application in motion control.
在讨论数字逻辑与神经元的关系后，提出一种利用前向三层神经网络实现任意布尔逻辑的设计方案。
After discussing the connection between digital logic and a neuron, a strategy of implementing arbitrary Boolean logic using three layers feedforward neural network is presented.
剖析二进神经元的逻辑意义对二进神经网络的规则提取是十分重要的。
For extracting rules from binary neural networks, it is important to analyze logical meaning of neurons.
研究了将神经网络与模糊逻辑融合交叉而形成的神经网络-模糊智能控制算法的特点和优越性。
In this paper, the characteristics and advantages of neuro fuzzy intelligent control algorithm, which is an intersection of neural networks and fuzzy logic, are studied.
神经网络和模糊逻辑都是有效的数据挖掘方法。
Both neural network and fuzzy logic are valid method for data mining.
应用模糊控制的逻辑推理性能，借助神经网络的学习能力，提出了一种模糊神经网络预测控制模型。
A fuzzy neural network prediction control model is stated by using the logic inference performance of fuzzy control and the learning ability of neural network.
近年来，基于神经网络和模糊逻辑的神经模糊控制得到了广泛的应用。
Recently, Neuro-fuzzy Control base on the Neural Network Theory and Fuzzy Logic System was used widely and successfully.
文章着重介绍模糊逻辑控制、神经网络控制以及它们的交叉结合的神经网络-模糊控制系统及其应用与设计。
Emphasis is put on the fuzzy logic control, neural network control, and both crossed neural network with fuzzy control system along with its application and design.
最后以实例验证了应用BP神经网络结合模糊逻辑和专家意见法进行主导产业的评价的准确性。
At last we use examples to verify the accuracy of the method that combines BP neural network with fuzzy logic and the expert advice to appraise the predominance industry.
最后以实例验证了应用BP神经网络结合模糊逻辑和专家意见法进行主导产业的评价的准确性。
At last we use examples to verify the accuracy of the method that combines BP neural network with fuzzy logic and the expert advice to appraise the predominance industry.
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