314 Abstract— Neuro-Fuzzy systems are hybrid intelligent systems which combine features of both paradigmsfuzzy logic and artificial neural networks. Adaptive Neuro Fuzzy Inference System (ANFIS) is one of such architecture which is widely used as solution for various real world problems. This paper describes development of an ANFIS model for FPGA implementation. Model can be realized with hardw...

The paper proposed the adaptive noise suppression technique for suppression of noise in voice communication. There are different techniques earlier used for adaptive filteration like least mean square, kalman’s filter etc.In the paper we used “fuzzy logic” technique for adaptive filteration. We know about the theory of adptive filteration of noise and application of fuzzy logic. We are using th...

This paper presents a new general purpose neuro-fuzzy controller to realize adaptive-network-based fuzzy inference system (ANFIS) architecture. ANFIS which tunes the fuzzy inference system with a back propagation algorithm based on collection of input-output data makes fuzzy system to learn. To implementing this idea we propose several improved CMOS analog circuits, including Gaussian-like memb...

The main goal of this research is to develop a novel optimum neuro-fuzzy system for diagnosis the complex and dynamic systems. .It has used the Particle Swarm Optimization (PSO) technique for training the Adaptive Neuro Fuzzy Inference System (ANFIS) off-line. The proposed system has applied for diagnosis the faults of two complex Photovoltaic (PV) systems. They are used to feed the power for l...

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated ...

some applications are critical and must designed fault tolerant system. usually voting algorithm is one of the principle elements of a fault tolerant system. two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. majority confronts with the problem of threshold limits and voter of weight...

The paper presents an adaptive neuro-fuzzy inference system (ANFIS) based modeling approach to predict the monthly global solar radiation (MGSR) in Bhubaneswar. Comparisons of the predicted and measured value of monthly global solar radiation (GSR) on a horizontal surface are presented. The input parameters of the model used in this paper are sunshine duration, temperature, humidity, clearness ...

The constant amplitude fatigue crack growth life is affected by load ratio which quantifies the influence of mean load. Several research works have been conducted to study the effect of load ratio on crack growth rate through deterministic approach. However, the application of artificial intelligence methods particularly adaptive neuro-fuzzy technique (ANFIS) is lacking. The current research pr...

The application of neuro-fuzzy inference system to predict the compressive strengths of concrete is presented in this study. To investigate the influence of various parameters which affect the compressive strength, 2000 data samples were used for the analysis. Adaptive neuro-fuzzy inference system (ANFIS) was introduced for training and testing the data obtained from technical literatures. To r...

This paper proposes two different approaches for the prediction of type2 diabetes. Many different techniques have been used for the prediction of chronic diseases by different researchers. Among them Adaptive Neuro Fuzzy Inference system (ANFIS) is very popular and already used for the prediction of type 2 diabetes. In this paper, the proposed system is optimization of ANFIS using Genetic Algor...