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.
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.
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.
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.
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.
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.
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.
在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。
The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.
从工业过程实际应用要求出发，研究开发了基于模糊逻辑系统的小脑模型关节控制器神经网络算法。
A new neural algorithm based on fuzzy Cerebella Model Articulation Controller (CMAC) is researched for the application of industry process.
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.
本论文对包含遗传算法、模糊逻辑控制和神经网络的软计算的智能控制及其几种不同结合方式做了较为系统的研究。
In this thesis, soft computing based control algorithms including genetic algorithms (GA), fuzzy control, neural networks (NN) and their different combinations are discussed systematically.
通常水下机器人的控制方式有PID控制器，神经网络控制器和模糊逻辑控制器三种。
PID control, neural control and fuzzy control, but all of them have different limitations.
本文还详细介绍了一种用多层前向神经网络实现模糊逻辑的自适应神经网络模糊推理系统——ANFIS，并用它来分析、验证神经模糊控制的控制效果。
This paper also stated the method of Adaptive Neural-Fuzzy Inference System (ANFIS) in details, which was used to analysis and testify effect of the NN-FC.
并结合模糊逻辑控制和神经网络控制的各自优点，设计温室模糊神经网络控制器。
Then, the controller based on fuzzy neural network for greenhouse system is designed through combining advantages of fuzzy logic and neural network.
针对金免疫层析定量测试的要求，将模糊逻辑与人工神经网络相结合，采用模糊神经网络隐式PID控制作为控温方法。
According to the requirement of the GICA strip quantitative detection system, the fuzzy neural networks PID is used by combining fuzzy logic and artificial neural network.
针对金免疫层析定量测试的要求，将模糊逻辑与人工神经网络相结合，采用模糊神经网络隐式PID控制作为控温方法。
According to the requirement of the GICA strip quantitative detection system, the fuzzy neural networks PID is used by combining fuzzy logic and artificial neural network.
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