نتایج جستجو برای: perceptron neural network was designed

تعداد نتایج: 4702949  

Journal: :journal of structural engineering and geo-techniques 2011
hassan aghabarati mohsen tabrizizadeh

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...

ژورنال: علوم آب و خاک 2019

Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficienc...

Journal: :international journal of advanced design and manufacturing technology 0
ahmad haghani department of mechanics, faculty of engineering, shahrekord branch, islamic azad university, shahrekord, iran

strip tearing during cold rolling process has always been considered among the main concerns for steel companies. several works have been done so far regarding the examination of the issue. in this paper, experimental data from cold rolling tandem mill is used for detecting strip tearing. sensors are placed across the cold rolling tandem mill. they receive information on parameters (such as ang...

Journal: :desert 2010
h. memarian khalilabad s. feiznia k. zakikhani

abstract erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. for this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual model ...

In order to river flow forecasting in catchments area in during many years are invented different methods that their efficiency is confirmed. One of these simulation models is neural network that it can draw the existence of truth together with considerable attention. In this research in order to Discharge simulation is investigated meteorological parameters effects on Ghare Aghaj river flow. F...

Journal: :international journal of agricultural management and development 2011
mohammad reza pakravan mohammad kavoosi kelashemi hamid reza alipour

in the present study iran’s rice imports trend is forecasted, using artificial neural networks and econometric methods, during 2009 to 2013, and their results are compared. the results showed that feet forward neural network leading with less forecast error and had better performance in comparison to econometric techniques and also, other methods of neural networks, such as recurrent networks a...

Mehran Kamkar Haghighi , Mostafa Langarizadeh, Rahil Hosseini Eshpala, Tabatabaei Banafsheh ,

Introduction: Artificial neural networks are a type of systems that use very complex technologies and non-algorithmic solutions for problem solving. These characteristics make them suitable for various medical applications. This study set out to investigate the application of artificial neural networks for differential diagnosis of thalassemia minor and iron-deficiency anemia. Methods: It is...

Mollapour, Y., Aghakhani, M., Azarioun2, H., Eskandari, H.,

This paper investigates the effect of boehmite nano-particles surface adsorbed byboric acid (BNBA) along with other input welding parameters such as welding current, arc voltage, welding speed, nozzle-to-plate distance on weld penetration. Weld penetration modeling was carried out using multi-layer perceptron artificial neural network (MPANN) technique. For the sake of training the network, 70%...

A. D. Safi Samghabadi, M. Nadershahi R. Tavakkoli-Moghaddam

Decision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore,...

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