Background: One of the leading causes of death is brain tumors. Accurate tumor classification leads to appropriate decision making and providing the most efficient treatment to the patients. This study aims to optimize brain tumor MR images classification accuracy using optimal threshold, PCA and training Adaptive Neuro Fuzzy Inference System (ANFIS) with different repetitions.Material and Meth...

This paper proposes an adaptive neurofuzzy interface system ANFIS approach to identify the real power transfer between generators. Based on solved load flow results, it first uses modified nodal equation method MNE to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to train the designed ANFIS. It also incorpor...

This study deals with the design of distributed power systems and optimal capacitor placement based on the ANFIS (Adaptive Network Fuzzy Inference Systems) using Mamdani-type fuzzy inference model. Traditionally, this problem of optimal capacitor placement has been solved through various optimization techniques, but it is less accuracy of finding placement and more time consuming. This can be a...

 Biodiesel production from non edible oil through transesterification in batch reactor is highly effective technique for kinetic analysis. Temperature, molar ratio, mixing intensity and catalyst influenced the biodiesel production and kinetic. Alkaline catalysts are more efficient in nature as compare to acid and base catalyst. This paper particularly focuses on the impact of NaOH catalyst o...

in the present study, a new modelling technique was developed for the modelling and analysis of hyperchaotic systems using an expert system based on wavelet decompositions and the adaptive neuro-fuzzy inference system (anfis). the success and superior properties of this new expert system were shown by applying the hyperchaotic chen system which is a hyperchaotic system. the obtained expert s...

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 ...

OBJECTIVES To develop and explore the predictability of patient perceptions of satisfaction through the hospital adoption of health information technology (HIT), leading to a better understanding of the benefits of increased HIT investment. DATA AND METHODS The solution proposed is based on comparing the predictive capability of artificial neural networks (ANNs) with the adaptive neuro-fuzzy ...

Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. Linear ARX modelling has widely been applied and satisfying result has been obtained, through linearization process. The objective of this paper is to compare ARX model ...

Motion prediction serves to improve quality of service for mobile hosts in mobile communication systems. Much work has been done to make motion prediction using statistical method or shadow clusters. In this study we try to attack this problem through the statistical method and ANFIS (adaptive neural-fuzzy inference system) method. In the simulation process, we generated mobile host motion patt...

Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and pe...