We propose a method for learning in multilayer perceptrons (MLPs). It includes new self-adapting features that make it suitable for dealing with a variety of problems without the need for parameter re-adjustments. The validity of our approach is benchmarked for two types of problems. The first benchmark is performed for the topologically complex parity problem with a number ofbinary inputs rang...

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...

this paper presents an accurate differential global positioning system (dgps) using multi-layered neural networks (nns) based on the back propagation (bp) and imperialistic competition algorithm (ica) in order to predict the dgps corrections for accurate positioning. simulation results allowed us to optimize the nn performance in term of residual mean square error. we compare results obtained b...

drying characteristics of green pea (pisum satium) with an initial moisture content of 76% (db) was studied in a fluidized bed dryer assisted by microwave heating. four drying air temperatures (30, 40, 50 and 60ºc) and five microwave powers (180, 360, 540, 720 and 900w) were adopted. several experiments were conducted to obtain data for sample moisture content versus drying time. the results sh...

—Regarding to the problems of low rate of convergence and fault saturation for neural network classifier based on the algorithm of error back propagation during the signal recognition, bee colony algorithm is applied in this paper so as to extract combined feature module of signal and suggest three different algorithms including algorithm with rapidly support, super self-adaption error back pr...

a back propagation artificial neural network (bpann) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. in this study, 261 gps/leveling and 8869 gravity intensityvalues of iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“bpann”, and “collocation” ...

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...

The static pull-in instability of beam-type micro-electromechanical systems is theoretically investigated. Two engineering cases including cantilever and double cantilever micro-beam are considered. Considering the mid-plane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, c...