Nonlinear system, advantages neural networks

Neural networks are applied in analytical chemistry in many and diverse ways. Used in calibration, ANNs have especially advantages in case of nonlinear relationships, multicomponent systems and single component analysis in case of various disturbances. 

The use of ANN is highly developed due their great advantage compared with traditional computing systems. ANNs have a flexible structiue, capable to make a nonlinear mapping between input and output data sets. In fact, multilayer perceptrons, one of the more extended neural network architectures, are imiversal approximators for complex problems [12]. The apphcation of this is reflected in the hteratiue devoted to prediction of many physical and chemical parameters, such as nanofluids density [14], density of binary mixtures of ionic hquids [15], electrical percolation temperatiue [16], molecular diffusivity of nonelectrolytes [17], vegetable oils viscosity [18], esters flash point prediction [12], polarity parameter in binary mixed solvents systems [19], etc. 

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