Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces computation time while also improving prediction accuracy model. In this paper, we propose a wavelength algorithm based on ant colony optimization (ACO), absolute value regression coefficient multiple linear (MLR) model used as basis for evaluating importance wavelengths, and after full MLR modeling in...

The present work describes a comparison of the ability of multiple linear regression (MLR) and artificial neural networks (ANN) to predict fish spatial occupancy and abundance in a mesotrophic reservoir. Models were run and tested with 306 observations obtained by the sampling point abundance method using electrofishing. For each of the 306 samples, the relationships between physical parameters...

In this work multiple linear regression (MLR) and artificial neural network (ANN) were used to predict the retention factors of 40 basic and neutral drugs in immobilized artificial membrane liquid chromatography. Two separate models were developed for prediction of solute retention in two mobile phase compositions which were used five identical descriptors. The standard errors in ANN calculatio...

Orally administered drugs must overcome several barriers before reaching their target site. Such barriers depend largely upon specific membrane transport systems and intracellular drug-metabolizing enzymes. For the first time, the P-glycoprotein (P-gp) and cytochrome P450s, the main line of defense by limiting the oral bioavailability (OB) of drugs, were brought into construction of QSAR modeli...

Estimating groundwater quality parameters through conventional methods is time-consuming laboratory measurements for megacities. There a need to develop models that can help decision-makers make policies sustainable reserves. The current study compared the efficiency of multivariate linear regressions (MLR) and artificial neural network (ANN) in prediction total dissolved solids (TDS) three sub...

The measurement and prediction of dye concentration is important in the design, planning and management of wastewater treatment. Soft computing techniques can be used as a support tool for analyzing data and making prediction. In this study, Central Composite Design (CCD) and adaptive neuro-fuzzy inference system (ANFIS) are employed to identify and predict the output intensity ratio of light t...