نتایج جستجو برای: neural network algorithm
تعداد نتایج: 1460261 فیلتر نتایج به سال:
Using Artificial Neural Network for Estimation of Density and Viscosities of Biodiesel–Diesel Blends
In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical ...
Most of existing researches for multi response optimization are based on regression analysis. However, the artificial neural network can be applied for the problem. In this paper, two approaches are proposed by consideration of both methods. In the first approach, regression model of the controllable factors and S/N ratio of each response has been achieved, then a fuzzy programming has been app...
In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...
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...
One of the most common and most dangerous diseases of blood fats are such as heart disease, diabetes and stroke, heart and brain. It can control the timely diagnosis, treatment and then prevention of complications is become very effective even without using medicine. Heart disease and diabetes file if patients has useful information that can be used to estimate blood fat timely diagnosis. In th...
Using Artificial Neural Network for Estimation of Density and Viscosities of Biodiesel–Diesel Blends
In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical ...
because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...
هدف پژوهش حاضر پیشبینی شاخص قیمت بورس اوراق بهادار تهران با استفاده از مدل شبکه عصبی هیبریدی مبتنی بر الگوریتم ژنتیک و جستجوی هارمونی است. مربوطترین نماگرهای تکنیکی به عنوان متغیرهای ورودی و تعداد بهینه نرون در لایه پنهان شبکه عصبی مصنوعی با استفاده از الگوریتمهای فراابتکاری ژنتیک و جستجوی هارمونی حاصل میگردد. مقادیر روزانه شاخص قیمت بورس اوراق بهادار تهران از تاریخ 1/10/91 الی 30/9/94 جهت ...
objective: in this study, artificial neural network (ann) analysis of virotherapy in preclinical breast cancer was investigated. materials and methods: in this research article, a multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated in order to develop a predictive model. the input parameters of the model were virus dose, week and tamoxifen ci...
Various artificial neural networks types are examined and compared for the prediction of surface roughness in manufacturing technology. The aim of the study is to evaluate different kinds of neural networks and observe their performance and applicability on the same problem. More specifically, feed-forward artificial neural networks are trained with three different back propagation algorithms, ...
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