P. A. Aguilera

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Kohonen neural network (KNN) was applied to nutrient data (ammonia, nitrite, nitrate and phosphate) taken from coastal waters in a Spanish tourist area. The activation maps obtained were not sufficient to evaluate and predict the trophic status of coastal waters. To achieve this aim, a new methodology is proposed which uses as its starting point the(More)
With the aim of obtaining an index of coastal water quality, a methodological procedure based on numerical classification and discriminant analysis is presented. The procedure was applied to nutrient data (ammonia, nitrite, nitrate, and phosphate) analyzed along the coastal waters of a Spanish tourist area. Using numerical classification, three levels of(More)
Dermal exposure to pesticides is one of the main sanitary problems which greenhouses workers face. With the dual aims of establishing both the body part that receives the greatest exposure and the variable that has greatest influence on this exposure level, 22 pesticide application trials were performed. Trials were carried out in different greenhouse(More)
We propose a new methodology based on continuous Bayesian networks for assessing species richness. Specifically, we applied a restricted structure Bayesian network, known as tree augmented naive Bayes (TAN), regarding a set of environmental continuous predictors. First, we analysed the relationships between the response variable (called the terrestrial(More)
Datasets with an excessive number of zeros are fairly common in several disciplines. The aim of this paper is to improve the predictive power of hybrid Bayesian network classifiers when some of the explanatory variables show a high concentration of values at zero. We develop a new hybrid Bayesian network classifier called zero-inflated tree augmented naive(More)