Multiobjective RBFNNs Designer for Function Approximation: An Application for Mineral Reduction

Radial Basis Function Neural Networks (RBFNNs) are well known because, among other applications, they present a good perfor- mance when approximating functions. The function approximation prob- lem arises in the construction of a control system to optimize the process of the mineral reduction. In order to regulate the temperature of the ovens and other parameters, it is necessary a module to predict the ¯nal concentration of mineral that will be obtained from the source materials. This module can be formed by an RBFNN that predicts the output and by the algorithm that designs the RBFNN dynamically as more data is obtained. The design of RBFNNs is a very complex task where many parameters have to be determined, therefore, a genetic algorithm that determines all of them has been developed. This algorithm provides sat- isfactory results since the networks it generates are able to predict quite precisely the ¯nal concentration of mineral.Spanish CICYT Project TIN2004-01419European Commission's Research Infrastructures RII3-CT-2003-506079 (HPC-Europa

Duroc and Iberian Pork Neural Network Classification by Visible and Near Infrared Reflectance Spectroscopy

a b s t r a c t Visible and near infrared reflectance spectroscopy (VIS/NIRS) was used to differentiate between Duroc and Iberian pork in the M. masseter. Samples of Duroc (n = 15) and Iberian (n = 15) pig muscles were scanned in the VIS/NIR region (350-2500 nm) using a portable spectral radiometer. Both mutual information and VIS/NIRS spectra characterization were developed to generate a ranking of variables and the data were then processed by artificial neural networks, establishing 1, 3, or 10 wavelengths as input variable for classifying between the pig breeds. The models correctly classified >70% of all problem assumptions, with a correct classification of >95% for the three-variable assumption using either mutual information ranking or VIS/NIRS spectra characterization. These results demonstrate the potential value of the VIS/ NIRS technique as an objective and rapid method for the authentication and identification of Duroc and Iberian pork