Construction of radial basis function networks with diversified topologies

In this review we bring together some of our recent work from the angle of the diversified RBF topologies, including three different topologies; (i) the RBF network with tunable nodes; (ii) the Box-Cox output transformation based RBF network (Box-Cox RBF); and (iii) the RBF network with boundary value constraints (BVC-RBF). We show that the modified topologies have some advantages over the conventional RBF topology for specific problems. For each modified topology, the model construction algorithms have been developed. These proposed RBF topologies are respectively aimed at enhancing the modelling capabilities of; (i)flexible basis function shaping for improved model generalisation with the minimal model;(ii) effectively handling some dynamical processes in which the model residuals exhibit heteroscedasticity; and (iii) achieving automatic constraints satisfaction so as to incorporate deterministic prior knowledge with ease. It is shown that it is advantageous that the linear learning algorithms, e.g. the orthogonal forward selection (OFS) algorithm based leave-one-out (LOO) criteria, are still applicable as part of the proposed algorithms

Applications of neural networks to control systems

Available from British Library Document Supply Centre- DSC:DX170496 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

High and intermediate sulphidation environment in the same hydrothermal deposit: the example of Au-Cu Palai-Islica deposit, Carboneras (Almeria)

No abstract available

Neural network models in greenhouse air temperature prediction

The adequacy of radial basis function neural networks to model the inside air temperature of a hydroponic greenhouse as a function of the outside air temperature and solar radiation, and the inside relative humidity, is addressed. As the model is intended to be incorporated in an environmental control strategy both off-line and on-line methods could be of use to accomplish this task. In this paper known hybrid off-line training methods and on-line learning algorithms are analyzed. An off-line method and its application to on-line learning is proposed. It exploits the linear-non-linear structure found in radial basis function neural networks.http://www.sciencedirect.com/science/article/B6V10-44NM87G-5/1/eece7333cd9cdc60d1a36eda697cbb9

Mineralogy and geochemistry of El Dorado epithermal gold deposit, El Sauce district, central-northern Chile

The El Dorado Au-Cu deposit is located in an extensive intra-caldera zone of hydrothermal alteration affecting Upper Cretaceous andesites of the Los Elquinos Formation at La Serena (≈ 29°47′S Lat., 70°43′W Long., Chile). Quartz-sulfide veins of economic potential are hosted by N25W and N20E fault structures associated with quartz-illite alteration (+supergene kaolinite). The main ore minerals in the deposit are pyrite, chalcopyrite ± fahlore (As/(As + Sb): 0.06−0.98), with electrum, sphalerite, galena, bournonite-seligmanite (As/(As + Sb): 0.21−0.31), marcasite, pyrrhotite being accessory phases. Electrum, with an Ag content between 32 and 37 at.%, occurs interstitial to pyrite aggregates or along pyrite fractures. Pyrite commonly exhibits chemical zonation with some zones up to 1.96 at.% As. Electron probe microanalyses of pyrite indicate that As-rich zones do not exhibit detectable Au values. Fluid inclusion microthermometry shows homogenization temperatures between 130 and 352 °C and salinities between 1.6 and 6.9 wt.% NaCl eq. Isotope data for quartz, ankerite and phyllosilicates and estimated temperatures show that δ18O and δD for the hydrothermal fluids were between 3 and 10‰ and between −95 and −75‰, respectively. These results suggest the mineralizing fluids were a mixture of meteoric and magmatic waters. An epithermal intermediate-sulfidation model is proposed for the formation of the El Dorado deposit

Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes

10.1038/s41467-019-12438-5Nature Communications111253

Author Correction: Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes (Nature Communications, (2020), 11, 1, (2539), 10.1038/s41467-019-12438-5)

10.1038/s41467-021-21077-8Nature Communications12182

Characterising the loss-of-function impact of 5’ untranslated region variants in 15,708 individuals

10.1038/s41467-019-10717-9Nature Communications111252