模糊神经网络

  • 网络fuzzy neural network;FNN;fnns;anfis
模糊神经网络模糊神经网络
  1. 运用模糊神经网络方法和神经网络方法(NN)进行混凝土强度预测和配合比优化设计;

    The approaches of FNN and artificial neural network ( NN ) are applied to predict strength and to design the mix proportion of concrete .

  2. 基于模糊神经网络和数据融合的结构裂纹故障诊断

    Fault diagnosis to structural crack based on FNN and Data Fusion

  3. B样条隶属函数的模糊神经网络研究

    Research on Neural Fuzzy Network Using B Spline Membership function

  4. 基于模糊神经网络的Agent反应器结构及实现

    Architecture and Realization of Agent Reactive Module Based on Fuzzy Neural Networks

  5. 文中针对旋转机械几种典型故障的诊断,将模糊神经网络方法与传统BP网络方法和模糊分类方法进行了比较。

    Several typical faults in rotating machinery are analyzed with the method .

  6. 基于H∞变结构的不确定机器人模糊神经网络控制

    Fuzzy neural-network control based on H_ ∞ variable structure control for uncertain robot manipulators

  7. 基于TS模糊神经网络的Fuzzy规则自动获取研究

    Research of automatic fuzzy rule extraction based on TS fuzzy neural networks

  8. 因此本设计选择B样条函数作为模糊神经网络控制器的隶属函数,以B样条函数为媒介将模糊控制与神经网络有机地结合起来,发挥各自优势,实现对控制器的优化。

    So by combination of fuzzy control and neural-networks with B-Spline functions , can advance both advantages to control the system .

  9. 然后,再运用BP算法优化模糊神经网络的连接权系数。

    Finally , the back propagation algorithm was used to optimize the connection coefficients of fuzzy neural network .

  10. 重点介绍了模糊神经网络PID算法在PLC控制器上的仿真实现方法。

    The paper is focus on the method of PLC simulation for RBF fuzzy neural network PID algorithm .

  11. 首先,使用遗传算法和BP算法相结合的方式来优化模糊神经网络;

    Firstly , the hybrid learning methods integrating genetic algorithm with BP algorithm to optimize fuzzy-neural network are employed .

  12. 然后采用BP算法对神经网络进行调节,从而确定出模糊神经网络的参数。

    Then adjusted the neural network by Back-Propagation ( BP ) algorithm , so the parameters of fuzzy neural network were determined .

  13. 提出了将基于模糊神经网络的PID控制策略用于电动助力转向系统中助力电机的控制。设计了电动助力转向试验台,并进行了电动助力转向系统的台架试验。

    A PDI control strategy based on fuzzy neural network is applied to the control of motor in electric power steering system .

  14. 该系统利用模糊神经网络调整PID参数,进一步完善了PID控制的自适应性能。

    Fuzzy_Neural Network is used to modulate PID parameters in this system , which further perfects the adaptive performance of PID control .

  15. 单体模糊神经网络:在智能控制中的应用及VLSI实现

    Monolithic Fuzzy Neural Network ( MFNNs ): Application in Intelligent Control & VLSI Realization

  16. 基于自学习模糊神经网络AMT车辆巡航控制

    Investigation on AMT vehicle cruise control using self-lear-ning fuzzy neural networks

  17. 混沌机制在T-S模型模糊神经网络的系统辨识研究

    Study on Chaotic Mechanism in System Identification Using T-S Model Fuzzy Neural Networks

  18. 基于Chebyshev基函数模糊神经网络的快速辨识方法

    Fast Identification Method of Fuzzy Neural Networks Based on Chebyshev Basis Function

  19. 永磁电机采用模糊神经网络和无位置传感器观测器的控制方法,利用数字信号处理器(DSP)实现运动过程的控制。

    The neuro-fuzzy scheme and position-sensorless control of the permanent-magnet motor is investigated , and the digital signal process ( DSP ) controls its movement .

  20. 一种改进型T-S模糊神经网络

    An Improved T-S Fuzzy Neural Network

  21. 介绍了利用模糊神经网络建立T-S模糊模型的方法;

    A fuzzy modeling method based on a fuzzy neural network of T S model is introduced .

  22. 导出故障原因计算模型和故障诊断数学模型,并采用改进的5层BP模糊神经网络求解。

    Calculation model of fault causation and mathematical model of fault diagnosis was educed , these models were calculated with improved BP fuzzy neural network with 5 layer .

  23. 提出基于T-S模糊神经网络的变结构控制方法。

    A variable structure control method based on T-S fuzzy neural network ( FNN ) is brought forward .

  24. 首先提出一种基于Agent封装的模糊神经网络结构,它能主动发现服务并进行自发互操作,多Agent之间能相互协调和协同工作;

    A kind of new belief measure structure , called fuzzy-neural network structure under the encapsulation of agent is presented , which can discover service proactively and supply spontaneous interoperation in cooperation with multi-agents .

  25. ANFIS实现的模糊神经网络在交通信号配时优化中的应用

    Fuzzy Neural Network Realized by ANFIS and Its Application to the Traffic Signal Timing Optimization

  26. 利用GA-BP算法对模糊神经网络进行优化

    Optimizing Fuzzy Neural Network Using GA-BP Algorithm

  27. 利用模糊神经网络避障控制器融合CCD摄像机与超声波传感器探测到的环境信息,以实现机器人的安全避障。

    In order to avoid the obstacles successfully , detection results from CCD and ultrasonic sensors are fused by a fuzzy neural network , which acts as an avoidance controller .

  28. 考虑了模糊神经网络的学习功能,提出利用Additivemultiplicative模糊神经网络(AMFNN)对ATM网络进行拥塞控制的方案。

    Based on additive-multiplicative fuzzy neural network ( AMFNN ), a novel congestion control scheme for ATM network is presented .

  29. 提出了一种宽带网络中基于模糊神经网络的连接接纳控制()方法,结合了模糊逻辑的语言控制能力和神经网络的自学习能CAC力。

    This paper proposes a fuzzy neural network approach for connection admission control ( FNN-CAC ) in broadband networks .

  30. 本文采用模糊神经网络算法对ATM网络进行连接接纳控制,仿真结果表明它比传统的算法有更好的效果。

    This paper brings the fuzzy neural network algorithms into the call admission control in ATM networks . The simulation result shows that it has better effect than usual algorithms .