这种特征可以综合运用神经网络、模糊数学等现代数学方法加以满意地描述，并在此基础上成功地开发了优化配煤专家系统。
This feature can be finely described by the way of neural network and fuzzy mathematics etc. in an effort to develop the computer based expert system for coal blend successfully.
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。
A fuzzy controller for ship steering based on RBF networks and genetic algorithms is designed.
为克服现有入侵检测存在的不足，本文从特征提取、模糊神经网络应用于入侵检测、算法优化等方面进行了系统研究。
To ride of the shortage of the id, we study on the extraction of the features, id method based on fuzzy neural network, and algorithm optimization and so on.
提出了一种基于混沌变量的多层模糊神经网络优化算法设计。
An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network.
最后，对模糊决策网络计划工期—成本优化方法进行了探讨。
At last, it studies the fuzzy duration-cost optimization of decision network planning.
应用神经网络技术分析了决策露天采矿工艺选择各因素的主次关系，通过模糊决策优化了露天采矿工艺方法。
This paper analyses the importance of each factors that decide the surface mining technology by using of the neural network, optimizes the surface mining technology by using of the fuzzy decision.
本文基于模糊数学规划及系统优化的观点研究了分组交换网络中分组路径的选择问题。
The problem of route selection of the packets in networks is studied based on the viewpoint of fuzzy mathematical programming and system optimization in this paper.
第三部分对基于混沌优化算法的模糊优选神经网络预测模型进行研究。
In the third part, the prediction model of fuzzy optimal selection neural network based on chaotic optimization algorithm is studied.
模糊神经网络的学习算法采用的是快速的粒子群优化算法。
A fast stochastic global optimization algorithm, particle group optimization algorithm, was used for training the fuzzy neural network.
使用模糊测度作为神经网络的目标函数可以有效地描述像素类别的不确定性，从而通过使其最小实现图像分类优化。
Use fuzziness measures as objective function of neural network can depict uncertainty of pixels' category validly so as to optimize image classification by minimizing the objective function.
本文针对单瓶颈节点网络，考虑两个饱和非线性因素，制定控制规则，寻找优化参数，设计模糊控制器。
In this paper, single bottleneck node network is considered. With two saturation factors, we make control rules, find optimal parameters and design the controller.
目前已广泛应用于函数优化，神经网络训练，模糊系统控制等领域。
Has been widely used in function optimization, training neural networks, fuzzy systems control, and other fields.
本文提出用模糊线性规划求解网络计划最低费用日程的优化方法。
This paper discusses an optimization method to determine the minimum cost scheduling in network schedule by means of fuzzy linear programming.
为了优化用于故障分类的多层前馈网络结构配置，提出了一种基于模糊逻辑的优化方法。
In order to optimize the design of MLP network structure for fault classification, an optimum approach based on fuzzy logic is presented.
给出了一个模糊网络最低成本日程优化的实例计算，通过实例计算说明了计算的新方法。
And it also presents an example calculation of optimizing minimum cost time limit for fuzzy network to explain this new method.
该算法分别采用神经网络模型进行模糊集隶属函数的表达及优化问题的求解，从而将模糊优化同神经网络有机地结合起来。
A new algorithm based on neural network models is also presented, in which the neural networks are employed to express the membership function of fuzzy sets and solve the optimization problems.
该模型直接计及了规划过程中所存在的模糊、随机因素对网络结构优化的影响。
In this model the effects of fuzzy and stochastic factors pertaining in the planning process are considered directly.
本文研究了模糊神经网络，用神经网络结构进行模糊推理，用BP算法调节和优化具有局部性的参数。
In this paper, fuzzy neural network was studied and fuzzy reasoning was realized by use of neural networks structure. BP algorithm is used to optimize local parameter.
目前微粒群算法已广泛应用于函数优化、神经网络训练、数据挖掘、模糊系统控制以及其他的应用领域。
Recently, Particle Swarm optimization is applied into function optimization, Neural Networks, data mining, Fuzzy Control System and other application field.
对每个控制模块设计了相应的模糊优化控制算法，并用改进的BP神经网络实现算法的模糊关系。
Fuzzy optimal control arithmetic was designed for each module, and an improved BP neural network was introduced to implement the fuzzy relation.
运用神经网络和模糊数学方法，建立基于模糊和神经网络的炸药与岩石匹配优化系统，并应用于工程实践。
The matching and optimizing system of rock and explosive based on fuzzy integration judge and neural network is established by use of neural network and fuzzy mathematical method.
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。
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.
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 relation between the input of FNN, such as disturbance, system state parameters, and output of FNN, optimal rescheduling strategy, is built by FNN.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
该系统的控制器采用模糊神经网络控制器，它的控制器参数采用模拟退火算法全局优化来对BP算法进行改进的混合方法。
The parameters of the fuzzy neural network controller are optimized by the mixed learning methods with BP algorithm and Simulated Annealing algorithm which improves BP algorithm.
该系统的控制器采用模糊神经网络控制器，它的控制器参数采用模拟退火算法全局优化来对BP算法进行改进的混合方法。
The parameters of the fuzzy neural network controller are optimized by the mixed learning methods with BP algorithm and Simulated Annealing algorithm which improves BP algorithm.
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