نتایج جستجو برای: combined neural network

تعداد نتایج: 1181623  

Reza Farokhzad, Reza Jelokhani Niaraki

Compressive strength and concrete slump are the most important required parameters for design, depending on many factors such as concrete mix design, concrete material, experimental cases, tester skills, experimental errors etc. Since many of these factors are unknown, and no specific and relatively accurate formulation can be found for strength and slump, therefore, the concrete properties ca...

Journal: :journal of computer and robotics 0
hengameh mahdavi faculty of computer and information technology engineering, qazvin branch, islamic azad university, qazvin, iran

prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. in this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

Journal: :تحقیقات مالی 0
عادل آذر دانشگاه تربیت مدرس سیروس کریمی دانشگاه ایلام

the aim of this paper is how to predict stock return by using accounting ratios and also by using the procedure of neural network. this paper has considered the prediction of stock return by using accounting ratios with two procedures, the artificial neural network and least square regression. the independent variables in this paper are accounting ratios and dependent variable of stock return, ...

ژورنال: طب کار 2019

Background: Faculty members are one of the main factors in the higher education system, that high level of occupational stress caused by educational, research, and executive duties makes them exposed to burnout. The purpose of this study is Forecasting burnout of faculty members of Yazd Payame Noor University using artificial neural network technique. Methods: The present research is descripti...

M.R. Hosseinzadeh Moghaddam S. Javad Mirabedini T. banirostam

    The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase a...

M.R. Hosseinzadeh Moghaddam S. Javad Mirabedini T. banirostam

    The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase a...

سید علی عظیمی محسن شفیعی نیک آبادی

Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For ...

Akram Avami Mahmoud Mousavi,

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 hidde...

A.R Mardookhpour

In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed dat...

H. Harandizadeh, M. M. Toufigh, V. Toufigh,

The prediction of the ultimate bearing capacity of the pile under axial load is one of the important issues for many researches in the field of geotechnical engineering. In recent years, the use of computational intelligence techniques such as different methods of artificial neural network has been developed in terms of physical and numerical modeling aspects. In this study, a database of 100 p...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید