State of the art in the neuro fuzzy field
نویسنده
چکیده
This document describes the architecture of neuro fuzzy systems. First part of the document provides a review of general notions of fuzzy logic, and structure of fuzzy systems. A procedure and different types of fuzzy reasoning are described. The second part is devoted to the neural networks and to the simplest model of artificial neuron. In the third part, the similarities and differences between fuzzy systems and neural networks are discussed as well as their advantages and drawbacks and reasons for merging these two approaches. Then, three models of fuzzy neurons are presented, their learning methods, and the general architecture of fuzzy feed forward neural network. At least, the applications and hardware and development tools are described.
منابع مشابه
Design of robust controller by neuro-fuzzy system in a prescribed region via state feedback
In this paper, first a new algorithm for pole assignment of closed-loop multi-variable controllable systems in a prescribed region of the z-plane is presented. Then, robust state feedback controllers are designed by implementing a neural fuzzy system for the placement of closed-loop poles of a controllable system in a prescribed region in the left-hand side of z-plane. A new method based on the...
متن کاملA NEURO-FUZZY GRAPHIC OBJECT CLASSIFIER WITH MODIFIED DISTANCE MEASURE ESTIMATOR
The paper analyses issues leading to errors in graphic object classifiers. Thedistance measures suggested in literature and used as a basis in traditional, fuzzy, andNeuro-Fuzzy classifiers are found to be not suitable for classification of non-stylized orfuzzy objects in which the features of classes are much more difficult to recognize becauseof significant uncertainties in their location and...
متن کاملAdaptive Neuro Fuzzy Sliding Mode Based Genetic Algorithm Control System to Control of a pH Neutralization Process
In this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (ANFSGA) controlsystem is proposed for a pH neutralization system. In pH reactors, determination and control of pH isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. An ANFSGA control system is designed to overcome the complexity of precisecontrol o...
متن کاملCoastal Water Level Prediction Model Using Adaptive Neuro-fuzzy Inference System
This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...
متن کاملReliability and Sensitivity Analysis of Structures Using Adaptive Neuro-Fuzzy Systems
In this study, an efficient method based on Monte Carlo simulation, utilized with Adaptive Neuro-Fuzzy Inference System (ANFIS) is introduced for reliability analysis of structures. Monte Carlo Simulation is capable of solving a broad range of reliability problems. However, the amount of computational efforts that may involve is a draw back of such methods. ANFIS is capable of approximating str...
متن کاملEvaluation of the Neuro-Fuzzy and Hybrid Wavelet-Neural Models Efficiency in River Flow Forecasting (Case Study: Mohmmad Abad Watershed)
One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the risk of flood damage. Considering the importance of river flow forecasting in water resources ma...
متن کامل