This paper presents the performance comparison between back propagation, recursive prediction error (RPE) and modified recursive prediction error (MRPE) algorithms for training multilayered perceptron networks. Back propagation is a steepest descent type algorithm that normally has slow convergence rate and the search for the global minimum often becomes trapped at poor local minima. RPE and MR...

suspended sediment estimation is an important factor from different aspects including, farming, soil conservation, dams, aquatic life, as well as various aspects of the research. there are different methods for suspended sediment estimation. this study aims to estimate suspended sediment using feed forward neural network with error back propagation with levenberg-marquardt back propagation algo...

Abstract: In this paper, a method for determination of refractive index in membrane of fuel cell on basis of three-longitudinal-mode laser heterodyne interferometer is presented. The optical path difference between the target and reference paths is fixed and phase shift is then calculated in terms of refractive index shift. The measurement accuracy of this system is limited by nonlinearity erro...

abstract: in this paper, a method for determination of refractive index in membrane of fuel cell on basis of three-longitudinal-mode laser heterodyne interferometer is presented. the optical path difference between the target and reference paths is fixed and phase shift is then calculated in terms of refractive index shift. the measurement accuracy of this system is limited by nonlinearity erro...

Back propagation neural network is successfully used in various fields, particularly in pattern recognition. Despite numerous applications, back propagation neural network`s design and optimization are developed by trial-and-error process, which is time-consuming. On the other hand, although a dataset may contain many features, these features may not be useful in a back propagation neural netwo...

This paper used error back propagation algorithm and regression analysis to analyze and predict untranslated and translated Nigeria Stock Market Price (NSMP). Nigeria stock market prices were collected for the periods of seven hundred and twenty days and grouped into untranslated and translated train, validation and test data. A zero mean unit variance transformation was used to normalize the i...

artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...

Various artificial neural networks types are examined and compared for the prediction of surface roughness in manufacturing technology. The aim of the study is to evaluate different kinds of neural networks and observe their performance and applicability on the same problem. More specifically, feed-forward artificial neural networks are trained with three different back propagation algorithms, ...