introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The ou...

This paper deals with artificial neural network (ANN) architecture, the multilayer Feed-forward (MLFF) network with back propagation learning. The training of an artificial neural network involves two passes. In the forward pass, the input signals propagate from the network input to the output. In the reverse pass the calculated error signals propagate backwards through the network where they a...

We present in this paper a system of English handwriting recognition based on 26-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 26-point feature extraction is introduced for extracting the features of the handwritten a...

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of na...

This paper uses nonlinear regression, Artificial Neural Network (ANN) and Genetic Programming (GP) approaches for predicting an important tangible issue i.e. scours dimensions downstream of inverted siphon structures. Dimensional analysis and nonlinear regression-based equations was proposed for estimation of maximum scour depth, location of the scour hole, location and height of the dune downs...

The major aim of processing satellite images is to prepare topical and effectivemaps. The selection of appropriate classification methods plays an important role. Amongvarious methods existing for image classification, artificial neural network method is ofhigh accuracy. In present study, TM images of 1987, and ETM+ images of 2000 and 2006were analyzed using artificial fuzzy ARTMAP neural netwo...

since a high toxicity of cyanide which use as a reagent in the gold processing plant, thiosulfate has been recognized as a environmental friendly reagent for leaching of gold from ore. after gold leaching process it's important for recovery of gold from solution using adsorption or extraction methods, one of these methods is activated carbon.the loading of gold from industrial thiosulfate solut...

this study investigates the correlations among the tensile strength, mineral composition, and textural features of twenty-ninesandstones from kouzestan province. the regression analyses as well as artificial neural network (ann) are also applied to evaluatethe correlations. the results of simple regression analyses show no correlation between mineralogical features and tensile strength.however,...