neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

abstract soil salinity within plant root zone is one of the most important problems that cause reduction in yield in agricultural lands. in this research, salinity in soil profile was simulated in tabriz irrigation and drainage network using saltmod and artificial neural networks (anns) models. based on initial spatial distribution of salinity in soil profile, studying area was divided to 4 dif...

sorption of flavor compounds to inner layer of polymer packages and subsequent diffusion results in loss of food flavor and consequently decreases shelf life and consumer acceptance of food stuffs which in turn causes major economic losses, so it is of utmost importance to research on diffusivity of these compounds in polymers to minimize negative effects of this phenomenon. in current research...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

there is little consensus on the corporate diversification-efficiency relationship in the diversification literature. according to the corporate diversification, firms have a tendency to get more market share with diversifying in the local segment or in the international market. theoretically, a contradictory exists between the profitable strategy and the value reducing strategy in the diversif...

over the last decade or so, artificial neural networks (anns) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. however, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. for this reason, this study aims at de...

the successful key of trading in the forex market is the selection of correct exchange in proper time based on an exact prediction of future exchange rate. foreign exchange rates are affected by many correlated economic, political and even psychological factors. therefore, in order to achieve a profitable trade these factors should be considered. the application of intelligent techniques for fo...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...