fnn

And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.

Furthermore, the residual algorithm is applied to the FNN learning, which guarantees the convergence and rapidity.

As one of FNN, RBF network is also widely used in many fields.

The new FNN is used in the control of hot rolling mill production and a satisfying result is obtained.

An optimization design method was proposed for a Fuzzy-Neural Network (FNN) structure based on chaotic variables.

This paper introduces some basic theories, model and methods of fuzzy logic, neural network, and FNN.

Then the structure and the joint weight of FNN could be changed after harmonics estimation. The performance of SCFNN is also optimized.

At last, the application of SL_FNN in induction motor control system is proposed.

Gradient descent algorithm is an efficient method to train FNN, and it can be realized in batch or incremental manner.

Simulation results show FNN by using the method has simpler structure and higher control precision.

So the theory of FNN is very important for the intelligent control.

Based on Fuzzy Neural Network(FNN), an intelligent adaptive sliding-mode guidance law is presented.

A new control scheme based on fuzzy neural network (FNN) for valve-controlled motor was presented.

FNN simulation indicates that the predicted results are more accurate than that estimated with traditional method.

In order to improve performances of fuzzy neural networks (FNN), a method of training FNN using particle swarm optimizers (PSO) is proposed.

Analysis of the Simulation for FNN Controller of a Permanent Magnet Synchronous Servo Motor

Improvement of a FNN Automatic Gear-shifting Control System for Construction Machinery

The Self-organizing FNN for Pattern Recognition of the Unequal Feature Dimensions

Study of adaptability on FNN in mine safety assessment

A Generalized FNN Equivalent Sliding Mode Control for Synchronous Servo System

Medicine Components Recognition of Traditional Chinese Pharmaceutical Medicine Based on FNN

FNN-based Intelligent Fault Diagnosis System for Vehicle Engine

Extended FNN Soft Sensor Model for Handling Qualitative Inputs

Reinforcement learning based on FNN and its application in robot navigation

Application of FNN to Mining Subsidence Prediction

Application of Compensatory FNN in Training of Fuzzy Rules

Expert intelligent synchronous control based on FNN for constant pressure regulating pump

FNN Adaptive Robust Control of Nonlinear Systems

Study on FNN in Classification of Cardiac Arrhythmia

T-S FNN and its Application in Active Cluster

Application of FNN in the Recognition of Force of Foot about Athlete

FNN-based assessment model for soft sensing outputs

Structure Optimization and Ensemble of FNN Based on Cooperative Coevolution

Optimizing neuronal activation function types based on GP in constructive FNN design

Intelligent Model of Student Diathesis Evaluation System Based on FNN

Training Algorithm for FNN Based on a Class of Nonlinear Property

Structure Changed FNN Based on High Order Spectral Reduction

Intersections'Traffic Light Control System Based on FNN

The FNN Control and It's Application to Chemical Fibre Industry

FNN Identifier Based on Real-Valued Genetic Algorithms

Research on Evaluation of Supply Chain Performance Based on FNN

Control of FNN Self - Adapting Coal Blending Based on Ash Feedback

Temperature Control of Cement Kiln Calciner Based on FNN

Car Fault Diagnosis System Based on FNN and Rule-based Inference

Forecast of Exhaust Noise for Diesel Engines Based on FNN

Stability analysis of rock slope based on FNN

Research on Mining Method of Spatial Data Based on FNN

Fault Diagnosis of Missile Based on FNN