نتایج جستجو برای: artificial neural network transformer loss and life

تعداد نتایج: 17087938  

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...

ژورنال: علوم آب و خاک 2020

In this study, we used the ARIMA time series model, the fuzzy-neural inference network, multi-layer perceptron artificial neural network, and ARIMA-ANN, ARIMA-ANFIS hybrid models for the modeling and prediction of the daily electrical conductivity parameter of daily teleZang hydrometric station over the statistical period of 49 years. For this purpose, the daily data for the 1996-2004 period we...

Journal: :محیط شناسی 0
حمید زارع ابیانه دانشگاه بوعلی سینا ، استادیار گروه مهندسی آب دانشکدة کشاورزی مریم بیات ورکشی دانشگاه بوعلی سینا ، دانش آموخته کارشناسی ارشد آبیاری و زهکشی دانشکدة کشاورزی سمیرا اخوان دانشگاه بوعلی سینا، استادیار گروه مهندسی آب دانشکدة کشاورزی محمد محمدی دانشگاه بوعلی سینا، کارشناس آبیاری

information on nitrate in groundwater resources requires periodic measurements are accurate. despite the measure in some areas due to sensitive social and health community are not reported. therefore, be informed of the status of each area of water quality, modeling is essential. the purpose of this study was the application of artificial neural network method for estimating nitrate and compare...

Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosag...

Journal: :international journal of advanced biological and biomedical research 2014
fatemeh almasi ali jafari asadolah akram mosen nosrati hadi afazeli

during the past few years, modeling in agriculture has attracted considerable attention. new modeling methods including neural networks are employed in various industries, and it is necessary that their use in agriculture be also considered. this research addressed the trend of energy use in broiler farms in alborz province and sought to model the trend of energy consumption and production in t...

2008
Eleftherios I. Amoiralis Pavlos S. Georgilakis Marina A. Tsili Antonios G. Kladas

This paper proposes a stochastic optimization method, based on ant colony optimization, for the optimal choice of transformer sizes to be installed in a distribution network. This method is properly introduced to the solution of the optimal transformer sizing problem, taking into account the constraints imposed by the load the transformer serves throughout its life time and the possible transfo...

A Amiri GH Rostampour Mehdi Nikoo Mohammad Nikoo, T Babaeinejad

Rivers are important as the main source of supply for drinking, agriculture and industry.However, drinking water quality in terms of qualitative parameters, is the most important variable. Studias and predicting  changes in quality parameters along a river, are one of the goals of water resources planners and managers. In this regard, many water quality models in order to maintain better water ...

اسماعیلی, محمدهادی , اسمعیلی, جواد , قائمیان, علی , محمد پور تهمتن, رضا علی,

Background and purpose: Since the human health is an essential issue in medical sciences, accurate predicting the individual's disease status is of great importance. Therefore, predicting with models minimum error and maximum certainty should be used. This study used artificial neural network model for predicting coronary artery disease (CAD) because it is more precise Comared to after models. ...

Fateme Rajati, Mansour Rezaei, Negin Fakhri, Soodeh Shahsavari,

Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

The present paper presented a methodology for prioritizing the innovative and entrepreneurial indicators using Multi Criteria Decision Making (MCDM) and Artificial Neural Networks (ANNs), taking into account three individual, organizational and cultural dimensions simultaneously in decision making procedure. This methodology has two main advantages: first, the speed of operation in the accounti...

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