In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating p...

In this study the Dissolved Air Flotation (DAF) system in oil refinery was investigated for the treatment of refinery wastewater. In order to investigate sytem a labratory scale rig was built. The aim is to remove some of the wastewater pollutant materials and data modeling of COD test.The effect of several parameters on flotation efficiency namely, saturator pressure, and coagulant dose, on CO...

Estimation of distribution algorithm for optimization of neural networks for intrusion detection system p. 9 Neural network implementation in reprogrammable FPGA devices-an example for MLP p. 19 A new approach for finding an optimal solution and regularization by learning dynamic momentum p. 29 Domain dynamics in optimization tasks p. 37 Nonlinear function learning by the normalized radial basi...

In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

This paper surveys Neuro fuzzy systems (NFS) development in biomedical field. Paper gives brief literature review of articles for last decade (2005-2015) which explores various Neuro Fuzzy System methodologies that have been developed during this period of time, their work done and deficiencies. Use of Neuro fuzzy integrated systems in various biomedical engineering applications is summarised. ...

This paper proposes a hybrid approach based on neuro fuzzy model and emotional learning for prediction of stock exchange market. Neuro fuzzy models are powerful in modeling and forecasting highly nonlinear and complex time series. The emotional Learning, which is successfully used in bounded rational decision making, is introduced as an appropriate method to achieve particular goals in the pred...

The design of a neuro-fuzzy system based on a radial basis function (RBF) network architecture and using support vector learning is considered. Typically, a neuro-fuzzy model structure is created from numerical data, however the common modeling techniques may introduce unnecessary redundancy into the rule base. It is of great interest to reduce the number of fuzzy rules. The proposed method pro...