today, students spend only 10 percent of their time in training centers and the major part of their time is spent in home, society and other places. however, significant events happen in this limited time. in addition to training and learning, they are prepared and educated to interact with society. education is an important issue in global educating and training systems. there are different ap...

runoff is one of the major components of calculating water resource processes and is the main issue in hydrology. many concept models are used to predict the amount of runoff, which in most cases depend on topographical and hydrological data. conventional models are not appropriate for areas in which there is little hydrological data. changes in runoff are nonlinear, meaning it is time & space ...

The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights. This layer-by-layer training strategy greatly improves convergence speed. However, in HWO, the desired net function actually evolves in the gradient direction, which inevitably reduces efficiency. In this paper, two i...

Today, students spend only 10 percent of their time in training centers and the major part of their time is spent in home, society and other places. However, significant events happen in this limited time. In addition to training and learning, they are prepared and educated to interact with society. Education is an important issue in global educating and training systems. There are different ap...

Hidden Markov models (HMM) are well known in speech recognition, where they are trained to recognize spoken words and even whole sentences. They are used to find the parameters of a so-called hidden model (usually a DTMC) by training it with observed output sequences. This paper introduces an approach to train stochastic Petri nets with the methods of HMM. As opposed to a DTMC, a stochastic Pet...

In this letter, we propose a multi-user detection scheme based on a hidden training sequence for DS-UWB systems. The hidden training sequence, which uses a fraction of the informative sequence’s transmitting power as training information, is utilized for the receiver filter adaptation and channel estimation. By using this, the proposed scheme offers increased bandwidth efficiency (no period ded...

Parallel perceptrons are a novel approach to the study of committee machines that allows, among other things, for a fast training with minimal communications between outputs and hidden units. Moreover, their training allows to naturally define margins for hidden unit activations. In this work we shall show how to use those margins to perform subsample selections over a given training set that r...

Neural networks have been massively used in regression problems due to their ability to approximate complex nonlinear mappings directly from input patterns. However, collected data for training networks often include outliers which affect final results. This paper presents an approach for training single hidden-layer feedforward neural networks (SLFNs) using weighted least-squares scheme which ...