نتایج جستجو برای: artificial neural networks
تعداد نتایج: 834162 فیلتر نتایج به سال:
The lack of sediment gauging stations in the process of wind erosion, caused of estimate of sediment be process of necessary and important. Artificial neural networks can be used as an efficient and effective of tool to estimate and simulate sediments. In this paper two model multi-layer perceptron neural networks and radial neural network was used to estimate the amount of sediment in Korsya o...
this paper reports on the use of artificial neural networks (ann) and partial least squareregression (pls) combined with nir spectroscopy (900-1700 nm) to design calibration models for thedetermination of sugar content in sugar beet. in this study a total of 80 samples were used as the calibration set,whereas 40 samples were used for prediction. three pre-processing methods, including multiplic...
Although CO2 injection is one of the most common methods in enhanced oil recovery, it could alter fluid properties of oil and cause some problems such as asphaltene precipitation. The maximum amount of asphaltene precipitation occurs near the fluid pressure and concentration saturation. According to the description of asphaltene deposition onset, the bubble point pressure has a very special imp...
Free swelling index (FSI) is an important parameter for cokeability and combustion of coals. In this research, the effects of chemical properties of coals on the coal free swelling index were studied by artificial neural network methods. The artificial neural networks (ANNs) method was used for 200 datasets to estimate the free swelling index value. In this investigation, ten input parameters ...
this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...
introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...
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 ...
abstract tax is one of the main sources of financing government budget. therefore, having a clear picture about the attainable amount of taxes are not only necessary for optimal allocation of scarce resources for tax collection, but also helps the government to develop precise tax collection programs .in this article, the structural features of the tax revenues series have first been examined i...
this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...
changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. the cognition of causes is very important, because the system can be diagnosed and fault tolerated. in this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. the main fe...
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