This paper deals problem of intelligent hybrid systems. Intelligent systems include neural networks (NN), fuzzy systems (FS) and genetic algorithms (GA). Each of these intelligent systems has certain properties (ability of learning, modelling, classifying, obtaining empirical rules, solving optimizing tasks ...) fitting specific kind of applications. Combination of these intelligent systems cre...

This paper is concerned with the data mining application to business process automation. A short tutorial on stages of financial analysis of an enterprise is given. A brief description of data mining components for financial analysis of an enterprise is presented in the paper. The main element of data mining application is fuzzy neural system. The structure of fuzzy neural system includes lingu...

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dyna...

In this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and Newton-Cotesmethods with positive coefficient for the solution of linear Fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. Here neural network isconsidered as a part of large field called neural computing orsoft computing. We propose alearning algorithm from ...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

Two new computing models, namely a fuzzy expert system and a hybrid neural network-fuzzy expert system for time series forecasting of electric load, are presented in this paper. The fuzzy-logic-based expert system utilizes the historical relationship between load and dry-bulb temperature, and predicts electric loads fairly accurately, 1-24 h ahead. In the case of the hybrid neural network-fuzzy...

Aiming at the characteristics which variable air volume air conditioning system is multi-variable, nonlinear and uncertain system, normal fuzzy neural network is hard to meet the requirements which dynamic control of multi-variable. In this paper, we put forward a recursive neural network predictive control strategy based on T-S fuzzy model. Through T-S fuzzy recursive neural network predictor ...

A robust self-organizing fuzzy-neural control (RSOFNC) system is proposed in this paper. The RSOFNC system is comprised of a self-structuring fuzzy neural network (SFNN) controller and a robust controller. The SFNN controller is the principal controller and the robust controller is designed to achieve tracking performance. In the SFNN controller design, a SFNN with the asymmetric Gaussian membe...

The authors propose an automated neuro-fuzzy system approach (with neural network subsystem) to power quality assessment incorporating equipment susceptibility patterns. The system is expected to handle dependencies between superposition of different disturbances and specific devices’ susceptibility to disturbances. Two neural network architectures were applied: a well known radial-basis neural...

Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IPprotocol. To implement the main f...