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。
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.
研究了模糊推理神经网络计算模型及其连续函数逼近能力。
This paper deals with the computational model for fuzzy reasoning neural network and its function approximation capability.
针对河流-三角洲储层沉积微相划分问题，提出了一种基于加权模糊推理神经网络的判别方法。
Focusing on the classification of sedimentary microfacies in fluvial delta reservoir, one diagnosis based on weighted fuzzy neural network is proposed.
在控制系统中，将贝叶斯概率引入到模糊rbf神经网络中，增强了系统的推理能力，提高了飞机各个航道位置的模拟伺服精度。
In the control system, Bayes probability is introduced in the fuzzy RBF neural network and it intensity the inference ability and increase the servo precision.
基于模糊推理和BP神经网络的故障诊断模块(系统)具备良好的故障诊断能力。
Faults diagnosis module based on blur discursion and BP nerve network is used here for its preferable ability of faults diagnosing.
该系统采用了故障逆向推理机制、模糊神经网络技术和软件自校准技术，有效地提高了系统的可靠性、灵活性。
Based on the technology of fault converse inference, fuzzy nerve network and software adjusting itself etc, this system's reliability and flexibility is greatly enhanced.
模糊推理和神经网络在信息融合领域的应用各有所长。
When applied to information fusion, neural networks and fuzzy inference have their own advantages and disadvantages.
提出一种新型的过热汽温控制方案，主控制器基于自适应神经网络模糊推理系统(ANFIS)进行设计。
A new superheated steam temperature control system design scheme is proposed, the main controller design is based on Adaptive Network-based Fuzzy Inference system (ANFIS).
其中在多重模糊推理神经网络中，通过求解模糊关系方程的方法来确定网络的权值。
In the neural network corresponding to multidimensional fuzzy inference, the weights are adjusted by means of solution to fuzzy relation equation.
本文介绍了一种具有快速学习算法、能够执行补偿模糊推理的补偿模糊神经网络。
The compensation fuzzy neural network (CFNN) with fast learning algorithm and compensation fuzzy inference is introduced in this paper.
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.
应用单层神经网络可以学习多变量模糊控制规则中的未知参数．还可由它来实现多变量模糊推理过程。
The parameters of me fuzzy control rules of me controller can be learned by the learning slgorithm of the neural netowrk. and the inference process can be realized by the network.
讨论了一个基于神经网络处理系统，实现了推理知识的自动获取和自适应模糊推理，具有很强的实用性。
A practical neural networks based classification system was discussed in this paper, in which automatic knowledge acquiring and fuzzy reasoning was realized.
通过补偿模糊推理和快速学习算法的引入，使得补偿模糊神经网络在性能上优于一般的模糊神经网络。
Through the introduction of compensatory fuzzy inference and quick arithmetic, the property of compensatory fuzzy neural networks is superior to that of common fuzzy neutral networks.
仿真实验结果表明，具有自适应神经网络的模糊推理系统控制的异步电机矢量控制系统不仅动态和稳态性能都得到提高，而且具有较强的鲁棒性。
Simulation results show that the induction motor vector control system with adaptive neuro-fuzzy inference system can improve the static and dynamic performance of the motor and has good robust.
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.
设计了一个简单的人工智能故障诊断系统模型，它包括知识库、模糊推理、神经网络和控制模块等。
A simple artificial intelligence system for fault diagnosis established in this paper. The system consists of knowledge base, fuzzy reasoning module, neural network module and control module.
自适应神经网络模糊推理系统(ANFIS)能基于数据建模，无须专家经验，自动产生模糊规则和调整隶属度函数。
Applying Adaptive Neural-Fuzzy Inference System (ANFIS) can produce fuzzy rules and adjust membership functions automatically based on data without experience of experts.
采用集成基于事例推理，模糊推理，模糊神经网络(FNN)等多种人工智能推理技术，建立了铝合金电阻点焊工艺参数设计系统。
A process parameters design system of resistance spot welding of aluminum alloys integrating case based reasoning, fuzzy inference and fuzzy neutral network (FNN) was developed.
该文应用自适应神经网络模糊推理系统的方法对一个典型系统进行建模仿真，并阐述这三个参数的寻优方法。
This paper gives the simulation example for modeling a typical system with Adaptive Neural-Fuzzy Inference system and expatiates the method for choosing these three parameters.
采用模糊神经网络方法进行磨削加工尺寸精度的控制，给出了模糊推理BP网络模型。
In the paper, fuzzy neural network method is used to control the size accuracy in grinding process and fuzzy inference BP-network model is produced.
利用神经网络实现模糊推理，运用了一种模糊高斯基函数神经网络，并用于两关节机器人的轨迹跟踪控制。
The fuzzy inference is realized by neural network, a fuzzy Gauss function neural network is used for two-joint robot tracking control.
整个网络既有神经网络的学习能力，又有模糊系统的基于规则的推理能力，特别是对子类的自动聚类能力。
The whole network has not only the learning ability to neural network, but also the logic ability to fuzzy system based on rules, especially the automatic clustering ability to sub-class.
针对河流-三角洲储层沉积微相的划分问题，提出了基于加权模糊推理神经网络的判别方法。
Based on the division of river-delta reservoir sedimentary facies, we present a distinguishing method based on the fuzzy reasoning NN.
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 process of submarine decision control is a representative fuzzy process. FNN can properly deal with fuzzy information and has consequence ability.
在区间值模糊推理的理论基础上，提出了基于区间值推理的模糊神经网络。
Based on the interval value fuzzy reasoning (IVFR), the fuzzy neural network is proposed.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
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