A new optimal design based on fuzzy genetic algorithms is proposed in this paper, which can help to find the optimal value overall situation and reduce the calculating work.
本文提出一种模糊遗传算法的优化设计方法，能够迅速找到全局最优解，并加快收敛速度和减少计算工作量。
A fuzzy controller for ship steering based on RBF networks and genetic algorithms is designed.
设计了一种基于RBF网络和遗传优化的船舶操纵模糊控制器。
So, at last, Genetic Algorithms are capitalized on to optimize the membership functions of the input and output linguistic variables of the fuzzy controller so as to better its performance.
所以，本论文最后采用了遗传算法对输入输出语言变量的隶属函数进行优化以改善模糊控制器的性能。
This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.
本文提出一种基于基因算法优化的自学习模糊控制器的设计。
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.
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。
Moreover, a new fast learning method of fuzzy systems both based on genetic algorithms and gradient method is proposed.
实现了一种新的基于遗传算法和梯度下降方法的快速模糊系统学习算法。
First, a fuzzy controller is constructed according to pilot's driving experience and the parameters are optimized via the genetic algorithms.
首先，我们根据飞行员的驾驶经验构造了一个模糊控制器，并用遗传算法对其进行优化。
Mostly used methods are introduced in detail, including fuzzy method, rough sets theory, cloud theory, evidence theory, artificial neural networks, genetic algorithms and induction learning.
详细介绍了数据挖掘技术的常用方法，包括模糊理论、粗糙集理论、云理论、证据理论、人工神经网络、遗传算法以及归纳学习。
Takes a simple question for example to discuss how to apply the genetic algorithms to solve the multi-objectives and fuzzy problems.
就一个简单算例，着重探讨如何将遗传算法应用于解决多目标模糊问题。
At last, the thesis suggests using the method of Genetic Algorithms to optimize the rules of fuzzy control.
最后，论文提出采用遗传算法对模糊控制规则进行优化设计。
In this thesis, soft computing based control algorithms including genetic algorithms (GA), fuzzy control, neural networks (NN) and their different combinations are discussed systematically.
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。
We also propose novel ideas in optimizing the fuzzy control rules, using genetic algorithms.
在此基础上提出了采用遗传算法对压实参数模糊控制规则进行优化的新思路。
By using the genetic algorithms with hierarchical chromosome structures, rule generation and para - (meter) tuning of the fuzzy controller can be achieved simultaneously.
采用具有层次结构染色体编码方式的遗传算法来设计模糊控制器，实现了语言控制规则的自动生成和隶属函数参数的自动整定。
An optimal PID controller is proposed based on fuzzy inference and genetic algorithms, which is called the optimal fuzzy GA PID controller.
提出了一种基于模糊推理与遗传算法的最优PID控制器的设计方法。
A strategy based on genetic algorithms to design a fuzzy controller of a multi-input-multi-output (MIMO) structure-MR dampers system was presented here.
在这里的战略，提出了基于遗传算法设计模糊控制器的多输入多输出(MIMO)结构的磁流变阻尼器系统。
As the mathematic model of the wheeled mobile robot is very complicated, a GA (genetic algorithms) fuzzy neural network method is presented for its steering control.
针对数学模型复杂的轮式机器人的转向控制问题，使用基于遗传算法的模糊神经网络转向控制方法。
A new PID intelligent controller is proposed, combined with fuzzy logic controls and genetic algorithms, for AGC of interconnected power systems.
针对互联电力系统自动发电控制(agc)，结合模糊控制和遗传算法提出一种新型的PID智能控制器。
In this paper, a fuzzy logic control based on genetic algorithms for complex nonlinear vibration systems of multiple degree of freedom is proposed.
本文对于复杂的多自由度非线性振动系统提出了基于遗传算法的主动模糊控制方法。
On the basis of introducing conception and approach of Genetic Algorithms, the article analyzes the use of Genetic Algorithms in Neural network and Fuzzy Control.
文章在介绍遗传算法的概念、实现方法的基础上，分析了遗传算法在神经网络及模糊控制中的应用。
An approach to the technology with fuzzy systems, neural networks and genetic algorithms is given.
本文应用基于遗传算法的模糊神经网络方法，建立了科研项目立项评审的智能管理系统。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
Genetic Algorithms is used in solving the mathematical model, it can obtain the global optimum even if there exists local optimums, and enlarge the application range of Fuzzy Physical Programming.
利用遗传算法求解数学模型，解决了最终优化目标可能存在多个局部最优解的问题，拓宽了模糊物理规划的应用范围。
Genetic Algorithms, Neural Network and Fuzzy Control are important research fields in artificial intelligence.
遗传算法、神经网络与模糊控制是当前人工智能中的主要研究领域。
And then the OPF model is changed into fuzzy using the flexible restrictions, and is operated on by the improved Genetic Algorithms.
使用基于分布式母线，并考虑经济约束的最优潮流(opf)模型，利用其可伸缩约束条件进行模糊化处理，运用改进遗传算法求解最优潮流。
And then the OPF model is changed into fuzzy using the flexible restrictions, and is operated on by the improved Genetic Algorithms.
使用基于分布式母线，并考虑经济约束的最优潮流(opf)模型，利用其可伸缩约束条件进行模糊化处理，运用改进遗传算法求解最优潮流。
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