In this paper, an adaptive neuro fuzzy interference (ANFIS) based hybrid field oriented speed controlling of an induction motor is proposed. The proposed hybrid field oriented speed controller results attractive performance of induction motor with the potential features of both Artificial Neural network (ANN) and Fuzzy Logic Controller (FLC). In this topology the Artificial Neural Network (ANN)...

Adaptive Neuro-fuzzy inference system (ANFIS) is multi-layer system proposed by Jang, enables to increase the performance by integrates the best features of Artificial Neural Networks and Fuzzy inference system into a single framework. It is a popular framework for solving complex problems. In this present work, an ANFIS is proposed for detection the risk factor of hypertension. In this work, f...

the oxidative coupling of methane (ocm) performance over na-w-mn/sio2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (anfis) using reaction data gathered in an isothermal fixed bed microreactor. in the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (ghsv), and reaction temperature were conside...

In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of internal carotid artery stenosis and occlusion. The internal carotid arterial Doppler signals were recorded from 130 subjects that 45 of them suffered from internal carotid artery stenosis, 44 of them suffered from internal carotid artery occlusion and the rest of them were health...

slope stability analysis is an enduring research topic in the engineering and academic sectors. accurate prediction of the factor of safety (fos) of slopes, their stability, and their performance is not an easy task. in this work, the adaptive neuro-fuzzy inference system (anfis) was utilized to build an estimation model for the prediction of fos. three anfis models were implemented including g...

Abstract Electroencephagram (EEG) is the recording of electrical activity of the brain. Though it is intended to record cerebral signals,it also records the signals that are not of cerebral origin called artifacts. Artifact removal from EEG signals is essential for better diagnosis. This paper proposes a hybrid learning algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for elimin...

in this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (anfsga) controlsystem is proposed for a ph neutralization system. in ph reactors, determination and control of ph isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. an anfsga control system is designed to overcome the complexity of precisecontrol o...

Handwritten character recognition is an area with many applications. Over the last decade much research has gone into algorithms to develop systems, which accurately convert images of handwriting to text. At the same time, neuro-fuzzy classification models have been researched and proven to solve complex problems. In this paper, two popular models, Adaptive Neuro-Fuzzy Inference System (ANFIS) ...

This paper proposes an approach to tune an Adaptive Neuro Fuzzy Inference System (ANFIS) inverse controller using Iterative Learning Control (ILC). The control scheme consists of an ANFIS inverse model and learning control law. Direct ANFIS inverse controller may not guarantee satisfactory response due to different uncertainties associated with operating conditions and noisy training data. In t...

This paper presents a rotor position estimation technique for a 6/4 switched reluctance machine based on Adaptive Neuro fuzzy Inference System (ANFIS). This technique is applied for modelling the nonlinear rotor position of SRM using the magnetization characteristics of the machine. ANFIS has a strong nonlinear approximation ability which could be used for nonlinear modelling and its real time ...