Comparison of on-line learning algorithms for RBF models in greenhouse environmental control problems

The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

Thesis abstract. Applying species distribution modeling for the conservation of Iberian protected invertebrates

This article outlines the approaches to modeling the distribution of threatened invertebrates using data from atlases, museums and databases. Species Distribution Models (SDMs) are useful for estimating species’ ranges, identifying suitable habitats, and identifying the primary factors affecting species’ distributions. The study tackles the strategies used to obtain SDMs without reliable absence data while exploring their applications for conservation. I examine the conservation status of Copris species and Graellsia isabelae by delimiting their populations and exploring the effectiveness of protected areas. I show that the method of pseudo‐absence selection strongly determines the model obtained, generating different model predictions along the gradient between potential and realized distributions. After assessing the effects of species’ traits and data characteristics on accuracy, I found that species are modeled more accurately when sample sizes are larger, no matter the technique used.

Modeling the suitable habitat of a structural red gorgonian species in the Mediterranean/east Atlantic regions predicts a wider distribution than previously known

Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Univerdade do Algarve, 2015