Information extraction from satellite images is a challenging task. This is because of the associated uncertainty arising out of improper capture and subsequent transfer. Fuzzy systems are suitable for such applications because of the fact that these have the ability to capture minute variations in the patterns presented. Fuzzy systems are expert decision making tools that require support from ...

This paper presents an application of Adaptive Neuro-Fuzzy Inference System (ANFIS). The control structure of the purposed consists fuzzy logic to damp the low frequency oscillations of power system and neuro identifier to track the dynamic behavior of the plant. In practical for damping of disturbance in the power system, Automatic Voltage Controller (AVR) is used. To develop this controller a...

-In this paper, we analyze the impact of extinction ratio (Ron/off) of Mach-Zehnder (MZ) amplitude modulator using Fuzzy logic generator. The system performance has been analyzed by varying the value of extinction ratio (Ron/off) from 0 to 10 dB. It is found that the system gives optimum performance at extinction ratio value 9.965 dB. Further, the fuzzy model of the system is developed using AN...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System (ANFIS). We examine the period 1950-2009, where we take as the in-sample or training period 1950-2005, ...

In this study, a new adaptive controller is proposed for position control of pneumatic systems. Difficulties associated with the mathematical model of the system in addition to the instability caused by Pulse Width Modulation (PWM) in the learning-based controllers using gradient descent, motivate the development of a new approach for PWM pneumatics. In this study, two modified Feedback Error L...

In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) method based on the Artificial Neural Network (ANN) is applied to design an Inverse Kinematic based controller forthe inverse kinematical control of SCORBOT-ER V Plus. The proposed ANFIS controller combines the advantages of a fuzzy controller as well as the quick response and adaptability nature of an Artificial Neural Network (AN...

This paper introduces the configuration and investigation of Neuro-Fuzzy controller taking into account Adaptive Neuro-Fuzzy Inference System (ANFIS) structural engineering for Load recurrence control of a segregated wind-smaller scale hydro-diesel half and half power framework, to manage the recurrence deviation and force deviations. Because of the sudden burden changes and discontinuous wind ...

This paper compares the accuracy of three hybrid intelligent systems in forecasting ten international stock market indices; namely the CAC40, DAX, FTSE, Hang Seng, KOSPI, NASDAQ, NIKKEI, S&P500, Taiwan stock market price index, and the Canadian TSE. In particular, genetic algorithms (GA) are used to optimize the topology and parameters of the adaptive time delay neural networks (ATNN) and the t...

Peak ground acceleration (PGA) plays an important role in assessing effects of earthquakes on the built environment, persons, and the natural environment. It is a basic parameter of seismic wave motion based on which earthquake resistant building design and construction are made. The level of damage is, among other factors, directly proportional to the severity of the ground acceleration, and i...

This paper presents a three-phase hybrid power filter based on artificial intelligence control approach. It consists of C-type passive filter in parallel with a shunt active filter that is controlled by an adaptive Neuro-Fuzzy inference system (ANFIS) controller. The active filter is based on a three-phase voltage inverter with six control switches. The AC side of the filter is connected in par...