The paper presents a short review how to use feedforward neural networks for non-linear system identification, with application at the neural implementation of a fuzzy system. In this application the inputoutput transfer characteristics of the fuzzy system are used to evaluate the accuracy of the identification results expressed for a neuro-fuzzy model. This method could be used for identificat...

Adaptive control of nonlinear systems has been an active area in recent years, but it is difficult to control unknown plants. A common approach to deal with this problem is to utilize the simultaneous identification technique. Neural networks have been employed in the identification and control of unknown nonlinear systems owing to their massive parallelism, fast adaptation and learning capabil...

nowadays, credit risk is recognized as one of the most important bankruptcy factors of banks and financial institutions. in order to manage and control this risk, design of credit rating models is undeniable necessity. credit rating is used to identify the probability of credit default and on the other side classify the customers into two groups: good and bad accounts. until now, various statis...

The natural development of hybrid techniques causes biases with their roots in di erent technologies, in this case either in fuzzy systems or in neural networks. The neuro-fuzzy research is discussed in this paper giving examples and emphasising the neural network perspective. Introduction of new fuzzy systems models and the development of new neural learning algorithms could be observed in the...

In the present work an application of fuzzy neural networks for leather quality determination is investigated. An overview of the surface defects characteristics and their significance has been made. For leather quality estimation the most important features are the size and the location of the defects. These characteristics are measured using image analysis and they are used by fuzzy neural ne...

In this work neural and neuro-fuzzy controllers are developed for the inverters of Uninterruptible Power Supplies (UPS) to improve their transient response and adaptability to various loads. Idealized load-currentfeedback controller is built to obtain example patterns for training the networks. Example patterns under various loading conditions are used in the off-line training of the selected n...

The control effect of steam pressure is one of the most important factors influencing stability in chain type boiler. Aimed at the problem that the control of steam pressure is restricted by many factors, a kind of fuzzy neural network (FNN) is presented in this paper. The controller has the advantage of self-adapting, self-learning and tuning on-line. In simulation, this system exerts stably, ...

The paper compares the use of neural network and neurofuzzy approaches in diagnosis of endogenous intoxication syndrome. The comparison was carried out on real patient data. Data preprocessing, neural network design and experiments are reported. A fuzzy neural network and results of experiments with it are presented. The advantages of fuzzy neural network are shown.

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the applicatio...

The main purpose of this study was to develop and apply a neural network (NN) approach and an adaptive neuro-fuzzy inference system (ANFIS) model for forecasting the attendance rates at soccer games. The models were designed based on the characteristics of the problem. Past real data was used. Training data was used for training the models, and the testing data was used for evaluating the perfo...