Links between LVQ and Backpropagation
Pattern Recognition Letters
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Data Mining: A Knowledge Discovery Approach
Data Mining: A Knowledge Discovery Approach
Modeling durations of syllables using neural networks
Computer Speech and Language
Fuzzy neural network structure identification based on soft competitive learning
International Journal of Hybrid Intelligent Systems
Mortality assessment in intensive care units via adverse events using artificial neural networks
Artificial Intelligence in Medicine
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This paper presents an automatic system of neural networks (NNs) that has the ability to simulate and predict many of applied problems. The system architectures are automatically reorganized and the experimental process starts again, if the required performance is not reached. This processing is continued until the performance obtained. This system is first applied and tested on the two spiral problem; it shows that excellent generalization performance obtained by classifying all points of the two-spirals correctly. After that, it is applied and tested on the shear stress and the pressure drop problem across the short orifice die as a function of shear rate at different mean pressures for linear low-density polyethylene copolymer (LLDPE) at 190°C. The system shows a better agreement with an experimental data of the two cases: shear stress and pressure drop. The proposed system has been also designed to simulate other distributions not presented in the training set (predicted) and matched them effectively.