نتایج جستجو برای: artificial neural network

تعداد نتایج: 1026358  

There is a complicated relation between cold flat rolling parameters such as effective input parameters of cold rolling, output cold rolling force and exit thickness of strips. In many mathematical models, the effect of some cold rolling parameters has been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips, the ...

Journal: :مدیریت صنعتی 0
محمدرضا نیک بخت دانشگاه تهران مریم شریفی دانشگاه تهران

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

ژورنال: سلامت و محیط زیست 2015
جعفری , حمیده , رجایی, طاهر , رحیمی بنماران, رقیه,

Background & Objectives: The prediction and quality control of the Karaj River water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, performance of artificial neural network (ANN), combined wavelet-neural network (WANN), and multi linear regression (MLR) models were evaluated to predict next month nitrate and dissolved oxygen of “Pole K...

Journal: :اکو هیدرولوژی 0
سید جواد ساداتی نژاد دانشیار دانشکدۀ علوم و فنون نوین، دانشگاه تهران محمدرضا شکاری دانشجوی دکتری بیابان زدایی، دانشکدۀ منابع طبیعی و علوم زمین، دانشگاه کاشان عباسعلی ولی دانشیار دانشکدۀ منابع طبیعی و علوم زمین، دانشگاه کاشان

many of the meteorological variables such as precipitation, strongly depend on the large scale atmospheric and ocean surface circulations.in the current study, the effect of climatic signals on the average monthly rainfall of the adjacent stations of sheshdeh and gharebolagh area was investigated during the statistical period twenty five years from 1985 to 2009. the regression and neural networ...

Journal: :علوم دامی 0
حمیدرضا میرزایی دانشیار ، دانشگاه پیام نور، مشهد، ایران محمّد صالحی دیندارلو دانش آموخته کارشناسی ارشد علوم دامی، دانشگاه زابل

three artificial neural networks (ann) models; general regression neural network (grnn), redial basis function (rbf) and three layer multiple perceptron network were carried out to evaluate the prediction of the apparent metabolizable energy (ame) of wheat and corn from its chemical composition in broiler. input variables included: gross energy (ge), crude protein (cp), crude fiber (cf), ether ...

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, ...

Journal: :Journal of the Japan Society for Precision Engineering 2013

There is a complicated relation between cold flat rolling parameters such as effective input parameters of cold rolling, output cold rolling force and exit thickness of strips. In many mathematical models, the effect of some cold rolling parameters has been ignored and the outputs have not a desirable accuracy. In the other hand, there is a special relation among input thickness of strips, the ...

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...

Abazar Solgi, Feridon Radmanesh Heidar Zarei Vahid Nourani

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

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