In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from inpu...

The Neural Network (NN) modelling and application to system identification, prediction and control was discussed for many authors [15]. Mainly, two types of NN models are used: Feedforward (FFNN) and Recurrent (RNN). The main problem here is the use of different NN mathematical descriptions and control schemes, according to the structure of the object model. For example, N a r e n d r a and P ...

Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...

Agriculture is the mother of all cultures. It played a vital role in the development of human civilization. But plant leaf diseases can damage the crops there may be economic losses in crops. Without knowing about the diseases affected in the plant, the farmers are using excessive pesticides for the plant disease treatment. To overcome this, the detected spot diseases in leaves are classified b...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...

In this paper, a standalone permanent magnet synchronous generator (PMSG) system is designed to generate power at maximum point (MPP). The variable speed operation of wind energy conversion consists PMSG, controlled rectifier and voltage source inverter co the load. Proportional integral (PI), sliding mode (SM), feed forward neural network (FFNN) control strategies are applied in field oriented...

In medical image processing, segmentation is an important and challenging task. It is classically used to identify object contours and extract the object from the image. Tumor Classification is an significant in medical image analysis since it provides information related to anatomical structures as well as possible anomalous tissues necessary to treatment planning and patient follow-up. In thi...

Abstract: Classification of the cervical cell is one of the most important and crucial tasks in the medical image analysis. Due to its importance, the aim of the paper is to investigate about the classification of Cervical Cell as Normal Cell or Abnormal Cell by using individual feature extraction method and combining individual feature extraction features method with the classification techniq...

In this present paper, the machine learning approach is used to optimize, model, and predict factors during drilling Nimonic C263 under dry mode. tough aero alloys, it required find a predictive model optimize in alloy before actual machining process. It helps avoid cost material cost. Experimental trails are planned based on Taguchi analysis, L27 orthogonal array was chosen. Speed, feed, angle...

Patients age has been estimated in healthy population by means of the heart rate variability (HRV) parameters to assess the potentiality of HRV indexes as a biomarker of age. A long-term analysis of HRV has been performed, computing linear time and frequency domain parameters as well as non-linear metrics, in a dataset of 113 healthy subjects (age range 20-85 years old). The principal component...