In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear...

This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and...

In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural net...

introduction: epilepsy is a clinical syndrome in which seizures have a tendency to recur. sodium valproate is the most effective drug in the treatment of all types of generalized seizures. finding the optimal dosage (the lowest effective dose) of sodium valproate is a real challenge to all neurologists. in this study, a new approach based on adaptive neuro-fuzzy inference system (anfis) was pre...

In this research paper, ANFIS modeling and validation of Vestas 660 kW wind turbine based on actual data obtained from Eoun-Ebn-Ali wind farm in Tabriz, Iran, and FAST is performed. The turbine modeling is performed by deriving the non-linear dynamic equations of different subsystems. Then, the model parameters are identified to match the actual response. ANFIS is an artificial intelligent tech...

This paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting the surface roughness in turning operation for set of given cutting parameters, namely cutting speed, feed rate and depth of cut. Two different membership functions, triangular and bell shaped, were adopted during the training process of ANFIS in order to compare the prediction accuracy of surface roughness by t...

In power systems, the constant frequency, voltage, and output are desired determine quality of generated electrical energy. Therefore, frequency control is crucial in systems. The parameters conventional controllers used generation plants determined according to system's characteristics at stage installation, they cannot adapt changing system dynamics as lifespan increases. Thus, studies on aut...

This paper deals with the implementation of the Adaptive neuro fuzzy inference system (ANFIS) on a Xilinx based Field Programmable Gate Array Spartan-3E. The implemented hardware is then used to efficiently calibrate the U-Tube manometer, in which the relation between the level of mercury and the Capacitance developed across the Copper Plates of the manometer is highly non-linear. This system s...

This paper describes the modelling and control of a pH neutralization process using a Local Linear Model Tree (LOLIMOT) and an adaptive neuro–fuzzy inference system (ANFIS). The Direct and Inverse model building using LOLIMOT and ANFIS structures is described and compared. The direct and inverse models of the pH system are identified based on experimental data for the LOLIMOT and ANFIS structur...