نتایج جستجو برای: artificial neural network ann

تعداد نتایج: 1040345  

In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as  amount  of  flow  intensity  ratio,  temperature,  residence  time,  and  pH  are  used  as  input  variables  of  the network,  whereas  the  extraction  yield  is  considere...

Tailor-made blanks are sheet metal assemblies with different thicknesses and/or materials and/or surface coatings. A monolithic sheet can be machined to make the required thickness variations that is referred as tailor machined blanks. Due to the thickness variation in tailor machined blanks, laser bending of these blanks is more complicated than monolithic plates. In this article, laser formin...

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...

C. S. Nwaouzru O. E. Charles-Owaba V. O. Oladokun

This study shows the usefulness of Artificial Neural Network (ANN) in maintenance planning and man-agement. An ANN model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. The model achieved an accuracy of over 70% in predicting the expected downtime.

Accurate simulation runoff process can have a significant role in water resources management and related issues. The inherent complexity of  this process makes difficult the use of physical and numerical models. In recent years, application of intelligent models is increased a powerful tool in hydrological modeling. The aim of this study was the application of the Gamma test to select the optim...

Journal: :journal of industrial engineering, international 2006
v. o. oladokun o. e. charles-owaba c. s. nwaouzru

this study shows the usefulness of artificial neural network (ann) in maintenance planning and man-agement. an ann model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. the model achieved an accuracy of over 70% in predicting the expected downtime.

A. Barazandeh A. Esmailizadeh M. Khorshidi-Jalali M.R. Mohammadabadi, O.I. Babenko

The artificial neural networks (ANN) are the learning algorithms and mathematical models, which mimic the information processing ability of human brain and can be used to non linear and complex data. The aim of this study was to compare artificial neural network and regression models for prediction of body weight in Raini Cashmere goat. The data of 1389 goats for body weight, height at withers ...

Journal: :راهبرد مدیریت مالی 0
شهاب الدین شمس استادیار مدیریت، دانشگاه مازندران بهروز عطایی کارشناس ارشد مدیریت بازرگانی (گرایش مالی)، دانشگاه مازندران

the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

Journal: :nutrition and food sciences research 0
hajar abbasi islamic azad university, esfahan branch (khorasgan), arghavanieh, jey st., esfahan, iran. post code: 81551-39998, p.o.box: 81595-158 seyyed mahdi seyedain ardabili department of food science and technology, faculty of agriculture and natural resources, science and research branch, islamic azad university, tehran, iran mohammad amin mohammadifar department of food science and technology, faculty of nutrition sciences, food science and technology / national nutrition and food technology research institute, shahid beheshti university of medical sciences, po box 19395-47471, tehran, iran zahra emam-djomeh transfer phenomena laboratory, department of food science, technology and engineering, faculty of agricultural engineering and technology, agricultural campus of the university of tehran, po box 4111, 31587-11167 karadj, iran

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

Journal: :journal of research in health sciences 0
negin-sadat mirian morteza sedehi soleiman kheiri ali ahmadi

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...

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