Approximation theory and feedforward networks
Neural Networks
Kolmogorov's theorem and multilayer neural networks
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Building neural networks
Neural Networks: A Comprehensive Foundation
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Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
An Algorithm for Automatic Design of Two Hidden Layered Artificial Neural Networks
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Design of neural networks for fast convergence and accuracy: dynamics and control
IEEE Transactions on Neural Networks
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The purpose of this contribution is to present a very effective strategy for the development of matrix solid phase dispersion (MSPD) extraction methodology for the determination of chlorinated compounds in fish using experimental design methods and artificial neural networks (ANNs). The MSPD extraction method of compounds is a preparation method that comprises sample homogenization, cellular disruption, fractionation and purification in a single process. Many parameters have to be taken care of when developing an MSPD extraction method because its performance is mainly affected by column packing and elution procedure. In this study, the best possible performance of MSPD has been achieved using experimental design and ANN modeling. The ANN used is a multilayer perceptron (MLP) trained with the standard error back propagation algorithm. Experimental results demonstrate that the proposed soft computing strategy is very effective, efficient and achieves very satisfactory results.