A new method for computing the resonant frequency of the circular microstrip antenna, based on the adaptive neuro-fuzzy inference system (ANFIS), is presented. A hybrid learning algorithm is used to identify the parameters of ANFIS. The results of the new method are in excellent agreement with the experimental results reported elsewhere.

The paper introduces various methods for classification like fuzzy logic, and its combination with artificial neural networks. Datasets from UCI Repository have been used for the implementation of classification models using Matlab 7.0 for Fuzzy Inference System(FIS) and Anfis and Matlab R2007b for Anfis with variable labels and different membership functions.

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon th...

Conventional control algorithms used in pH control systems give inefficient performance, leading to use of large mixers. To improve the neutralization control process, an ANFIS based advanced controller has been proposed. In this paper, method of design of adaptive controller based on neurofuzzy technique is presented. The method uses ANFIS methodology to 1 / 4

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

In this paper, an efficient and accurate method for tomatoes sorting will proposed. first we extract features from inputted tomato image and then accurate and appropriate decision on Classification tomatoes using fuzzy the mamdani inference, adaptive fuzzy neural network (anfis) methods for each of that image. In our proposed system adaptive fuzzy neural network (anfis) has less error and syste...

Utilizing MATLAB to develop graphical user interface in modeling of machining responses is a very rare case among researchers, especially for the complex and nonlinear machining processes. Since it is more complicated and time consuming for one to explore artificial intelligent tools to model a process or response using MATLAB due to unfamiliarity and phobia of programming, a new approach is ve...

Software Effort Prediction is the process of estimating the effort required to develop software. Effectively controlling the expensive investment of software development is achieved by accurately estimating the effort. Effort estimation at the early stage of software development is very difficult because of lot of uncertainty in input parameters which decides the software effort. Adaptive Neuro...

Detection and segmentation of Brain tumor is very important because it provides anatomical information of normal and abnormal tissues which helps in treatment planning and patient follow-up. There are number of techniques for image segmentation. Proposed research work uses ANFIS (Artificial Neural Network Fuzzy Inference System) for image classification and then compares the results with FCM (F...

Induction generator is the most common generator in wind energy systems because of its simplicity, ruggedness, little maintenance, price, etc. Thus, a novel design of an Adaptive Neuro-fuzzy Inference strategy(ANFIS) for analyzing some of the parameters such as frequency, voltage, current, etc. of the induction motor is presented in this paper. Induction motors are characterized by highly non-l...