permeability is a property of porous medium that quantifies rock capacity to transmit fluids. frequently, core based permeability data are not available either because of the borehole conditions or due to the high cost of coring. for these reasons, over the years attempts have been made to estimate permeability by alternative ways. permeability is an elusive parameter in hydrocarbon reservoirs ...

The Artificial Neural Network (ANN) is a powerful data-driven model that can capture and represent both linear and non-linear relationships between input and output data. Hence, ANNs have been widely used for the prediction and forecasting of water quality variables, to treat the uncertainty of contaminant source, and nonlinearity of water quality data. However, the initial weight parameter pro...

In the present work, an artificial neural network (ANN) model was used to study the quantitative structure retention relationship (QSRR) of retention index (RI) of some volatile compounds in natural cocoa and conched chocolate powder. Molecular structural descriptors are selected using genetic algorithm to construct the nonlinear QSRR models, kernel partial least squares PLS (KPLS) and Levenber...

Sedimentation in reservoirs is an important issue that should be considered for the reservoirs operation and useful life. In this study, application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) in prediction of the sediment release from the bottom outlet using semi-cylinder for different variables was evaluated. Dimensionless parameters such as dimens...

Thermal errors can have significant effects on CNC machine tool accuracy. The errors usually come from thermal deformations of the machine elements created by heat sources within the machine structure or from ambient change. The performance of a thermal error compensation system inherently depends on the accuracy and robustness of the thermal error model. In this paper, Adaptive Neuro Fuzzy Inf...

Despite several individual forecasting models that have been proposed in the literature, accurate forecasting is yet one of the major challenging problems facing decision makers in various fields, especially financial markets. This is the main reason that numerous researchers have been devoted to develop strategies to improve forecasting accuracy. One of the most well established and widely use...

Predictive quantitative structure–activity relationship was performed on the novel 4-oxo-1,4-dihydroquinoline and 4-oxo-4H-pyrido[1,2-a]pyrimidine derivatives to explore relationship between the structure of synthesized compounds and their anti-HIV-1 activities. In this way, the suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections ...

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...

Predictive quantitative structure–activity relationship was performed on the novel 4-oxo-1,4-dihydroquinoline and 4-oxo-4H-pyrido[1,2-a]pyrimidine derivatives to explore relationship between the structure of synthesized compounds and their anti-HIV-1 activities. In this way, the suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections ...