نتایج جستجو برای: artificial neural network and genetic programming

تعداد نتایج: 17059087  

Introduction: Protein kinase causes many diseases, including cancer; therefore, inhibiting them plays an important role in the treatment of many diseases. Traditional discovery inhibitors of this enzyme is a time-consuming and costly process. Finding a reliable computer-aided drug discovery tools which can detect the inhibitors will reduce the cost. In this study, it is attempted to separate ki...

Journal: :محیط شناسی 0
روح اله نوری محمد علی عبدلی اشکان فرخ نیا آلاله قائمی

quantitative prediction of municipal solid waste generation has an important role in the optimization and programming of municipal solid waste management system. but, this concept was companied with many problems, because of the non homogenous nature and the effect of various factors out of the control on solid waste generation. in this study, the combination of artificial neural network and wa...

J. Karthick , K. Suguna, P. N. Raghunath, R. Uma Maheswari,

This study focuses on using an artificial neural network (ANN) based model for predicting the performance of high strength concrete (HSC) beams strengthened with surface mounted FRP laminates. Eight input parameters such as geometrical properties of the beam and mechanical properties of FRP laminates were considered for this study. Back propagation network with Lavenberg-Marquardt algorithm has...

Journal: :international journal of agricultural science and research 2011
h. abbasi z. emam-djomeh s. m. seyedin

farinograph is the most frequently used equipment for empirical rheological measurements of dough. it’suseful to illustrate quality of flour, behavior of dough during mechanical handling and texturalcharacteristics of finished products. the percentage of water absorption and the development time of doughare the most important parameters of farinography for bakery industries during production. h...

Journal: :journal of mining and environment 2014
s. bahrami f. doulati ardejani

in this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. novel hybrid method coupling artificial neural network (ann) with genetic algorithm (ga) called ann-ga, was utilised. ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (hh) in the observation w...

Journal: :iranian journal of chemistry and chemical engineering (ijcce) 2006
mahmoud mousavi akram avami

an artificial neural network has been used to determine the volume flux and rejections of ca2+ , na+ and cl¯, as a function of transmembrane pressure and concentrations of ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. the feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidden la...

Akhoondzadeh, Mahdi , Ranjbar, Sadegh,

Surface soil moisture is an important variable that plays a crucial role in the management of water and soil resources. Estimating this parameter is one of the important applications of remote sensing. One of the remote sensing techniques for precise estimation of this parameter is data-driven models. In this study, volumetric soil moisture content was estimated using data-driven models, suppor...

J Soltani Nabipour S M Hosseini Pooya S Nouri

Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients.Objective: This study evaluates the accuracy ...

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