Electricity has become an important concern in today’s society. This is due to the fact that electric grid now a greater number of non-linear components. The AC-powered locomotive one these aim this paper was model and predict reactive power produced by AC locomotive. presents study on modelling prediction locomotives. Reactive flow significant impact network voltage levels efficiency. research...

The aim of this paper is to propose an exploratory study on simple, accurate and 19 computationally efficient movement classification technique for prosthetic hand application. The 20 surface myoelectric signals were acquired from 2 muscles – Flexor Carpi Ulnaris and Extensor Carpi 21 Radialis of 4 normal-limb subjects. These signals were segmented and the features extracted using a 22 new comb...

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function ...

In this paper we presented an architecture and basic learning process underlying in fuzzy inference system and adaptive neuro fuzzy inference system which is a hybrid network implemented in framework of adaptive network. In real world computing environment, soft computing techniques including neural network, fuzzy logic algorithms have been widely used to derive an actual decision using given i...

Image segmentation is one of the vital steps in Image processing. It is a challenging task in segmenting MRI(Magnetic Resonance Imaging) images because these images have no linear features. But MRI images provide high quality when compared to any other imaging techniques, so it is best suited for clinical diagnosis, biomedical research, etc. This paper presents a novel approach for segmenting M...

Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent by individual sensor node is minimized .The cluster heads collect all sensed information from ...

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...

In this paper, a new segmentation method using hyperbolic tangent fuzzy cmeans (MHTFCM) algorithm for medical image segmentation. The proposed method uses two hyperbolic tangent functions for clustering of images. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI) and execution time (TM) under di...

Using a genetic algorithm owing to high nonlinearity of constraints, this paper first works on the optimal design of two-span continuous singly reinforced concrete beams. Given conditions are the span, dead and live loads, compressive strength of concrete and yield strength of steel; design variables are the width and effective depth of the continuous beam and steel ratios for positive and nega...

Fuzzy systems (FSs) are popular and interpretable machine learning methods, represented by the adaptive neuro-fuzzy inference system (ANFIS). However, they have difficulty dealing with high-dimensional data due to curse of dimensionality. To effectively handle ensure optimal performance, this paper presents a deep neural fuzzy (DNFS) based on subtractive clustering-based ANFIS (SC-ANFIS). Inspi...