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...

Lateral interactions are a key factor in the correct description of adsorption isotherms relevant to heterogeneous catalytic reactions. To model these lateral interactions, large number monolayer structures have be investigated, far exceeding limitations conventional techniques such as density functional theory. We developed new hybrid neural network that can substitute electronic structure cal...

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...

Artificial neural networks (ANNs) are processors that are trained to perform particular tasks. We couple a computational ANN with a simulated affective system in order to explore the interaction between the two. In particular, we design a simple affective system that adjusts the threshold values in the neurons of our ANN. The aim of this paper is to demonstrate that this simple affective system...