Artificial neural networks: fundamentals, computing, design, and application

Serum Concentration of Hepcidin as an Indicator of Iron Reserves in Children

“…SOS obtained with ANN models are of the same order of magnitude as experimental errors for outputs reported in the literature (24,25). ANN model is complex because of the high nonlinearity of the developed system (24,26).…”

“…The optimization procedures to minimize the error function between network and experimental outputs was used during ANN training cycle (23,24), and the sum of squares (SOS) was evaluated according to the BFGS algorithm, to speed up and stabilize convergence of the results (25). ANN models were used to predict experimental variables, reasonably well, for a broad range of the process variables.…”

Neural and Genetic Control Approaches in Process Engineering

“…As a result, the network assimilates information that can be recalled later. Neural networks are capable of handling complex and nonlinear problems, process information rapidly and can reduce the engineering effort required in controller model development (Basheer & Hajmeer, 2000).…”

“…The network input vector dimension was associated with the time window length selected for each input variable, which was dependent on distillation column dynamics and is usually chosen according to the expertise of process engineers (Basheer & Hajmeer, 2000). The hidden layer dimension was defined by using a trial and error procedure after selecting the input vector, while the net's output vector dimension directly resulted from the selected controlled variables.…”

Automated quality assessment of autonomously acquired microscopic images of fluorescently stained bacteria

“…The availability of large amounts of images offers the possibility to rapidly generate human made training sets and favors the application of such methods. One of these is the artificial neural network (ANN), a mathematical model inspired by the structure and behavior of animal neurons (8)(9)(10). It consists of interconnected layers of artificial neurons and has been successfully used to address a variety of scientific problems, from face recognition (11), protein phosphorylation site prediction (12), tumor diagnosis (13) to the classification of bacterial morphotypes (14).…”