نتایج جستجو برای: artificial neural network asphaltene
تعداد نتایج: 1026901 فیلتر نتایج به سال:
neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. hen...
Introduction: These days, there is a consensus that emotional intelligence plays an important role in the success of individuals in different areas of life. Persons with higher emotional intelligence had lower stress in dealing with demands and pressures in the workplace. The purpose of this study was to use artificial neural network to predict job stress and to compare the performance of this ...
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...
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...
background: clinically frank thyroid nodules are common and believed to be present in 4% to 10% of the adult population in the united states. in the current literature, fine needle aspiration biopsies are considered to be the milestone of a model which helps the physician decide whether a certain thyroid nodule needs a surgical approach or not. a considerable fact is that sensitivity and specif...
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...
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 ...
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. ...
in today’s business competitive world, decision makers of companies try to employ standard, efficient, theoretical and operational proven methods as a competitive advantage for making their critical strategic business decisions in order to survive in their industry. in this paper, a hybrid model based on fuzzy analytic hierarchy process (fahp) and artificial neural network (ann) is presented. t...
Introduction: Logistic regression is one of the modeling methods for bipartite dependent variables. On the other hand, artificial neural network is a flexible method with the least limitation. The importance of growing unnecessary beauty surgeries and the importance of prediction and classification made us consider the present study, with the aim of comparing logistic regression and artificial ...
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