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 ...

This paper presents an approach for modeling and prediction of both surface roughness and cutting zone temperature in turning of AISI304 austenitic stainless steel using multi-layer coated (TiCN+TiC+TiCN+TiN) tungsten carbide tools. The proposed approach is based on an adaptive neuro-fuzzy inference system (ANFIS) with particle swarm optimization (PSO) learning. AISI304 stainless steel bars are...

This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for fractal image compression. One of the image compression techniques in the spatial domain is Fractal Image Compression (FIC) but the main drawback of FIC using traditional exhaustive search is that it involves more computational time due to global search. In order to improve the computational time and compression rati...

A novel adaptive network fuzzy inference system (ANFIS) based filter is presented for the enhancement of images corrupted by random valued impulse noise (RVIN). This technique is performed in two steps. In the first step, impulse noise using an Asymmetric Trimmed Median Filter (ATMF). In the second step, image restoration is obtained by an appropriately combining ATMF with ANFIS at the removal ...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS), which has been adapted as an alternative to other classical models for estimating the vehicle delays at signalized junctions. Rules, fuzzification, and inference were modeled by ANFIS. In this model, a hybrid algorithm was used for training and tests. The artificial network used three input variables representing simulation o...

In medical image analysis, classification plays an imperative role and the accessible corporeal classification plunge to congregate the requisites. Automatic image classification is emergent thriving research area and contribution diagnostician for malady to ascertain the echelon of malignant cells of brain tumor using artifical intellect Since manual classification is time devastating and best...

Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging a...

Electrical load forecasting is well-known as one of the most important challenges in the management of electrical supply and demand and has been studied extensively. Electrical load forecasting is conducted at different time scales from short-term, medium-term and long-term load forecasting. Adaptive neuro-fuzzy inference system is a model that combines fuzzy logic and adaptive neuro system and...

An adaptive neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet works. The ANFIS model was employed to calculate vent air discharge in different gate openings for an embankment dam. A hybrid learning algorithm obtained from combining back-propagation and least square estimate was adopted to identify linear and...

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...