Encontrados 11 documentos, a visualizar página 1 de 2
Feature selection for bankruptcy prediction : a multi-objective optimization ap...
Mendes, F.; Duarte, J.; Vieira, Armando; Gaspar-Cunha, A.; Ribeiro, Bernardete; Ribeiro, André M. S.; Neves, João CarvalhoIn this work a Multi-Objective Evolutionary Algorithm (MOEA) was applied for feature selection in the problem of bankruptcy prediction. The aim is to maximize the accuracy of the classifier while keeping the number of features low. A two-objective problem - minimization of the number of features and accuracy maximization – is fully analyzed using two classifiers: Support Vector Machines and Logistic Function. A...
Financial distress model prediction using SVM +
Ribeiro, Bernardete; Silva, C.; Vieira, Armando; Gaspar-Cunha, A.; Neves, JoãoFinancial distress prediction is of great importance to all stakeholders in order to enable better decision-making in evaluating firms. In recent years, the rate of bankruptcy has risen and it is becoming harder to estimate as companies become more complex and the asymmetric information between banks and firms increases. Although a great variety of techniques have been applied along the years, no comprehensive ...
Multi-objective evolutionary algorithms for feature selection : application in ...
Gaspar-Cunha, A.; Mendes, F.; Duarte, J.; Vieira, Armando; Ribeiro, Bernardete; Ribeiro, André M. S.; Neves, João CarvalhoA Multi-Objective Evolutionary Algorithm (MOEA) was adapted in order to deal with problems of feature selection in datamining. The aim is to maximize the accuracy of the classifier and/or to minimize the errors produced while minimizing the number of features necessary. A Support Vector Machines (SVM) classifier was adopted. Simultaneously, the parameters required by the classifier were also optimized. The vali...
Efeito caotrópico do íon lítio na permeabilidade da cápsula polissacarídica da ...
Nordi,Cristina Souza Freire; Cavagliere,Thays Gabrielle Wenzel Ferreira; Vieira,Armando Augusto Henriques; Nascimento,Otaciro RangelO objetivo deste trabalho foi investigar o efeito caotrópico do íon Li+ na cápsula polissacarídica da microalga colonial Ankistrodesmus gracilis. Esta microalga possui uma cápsula extensa e contínua que envolve completamente as células. Neste estudo, foram utilizados a técnica de Ressonância Paramagnética Eletrônica (RPE) e o marcador de spin - Tempo (2,2,6,6-tetrametilpiperidine-1-oxil), de natureza não reativ...
Effect of polysaccharide capsule of the microalgae Staurastrum iversenii var. a...
Freire-Nordi,Cristina S.; Vieira,Armando A. H.; Nakaie,Clovis R.; Nascimento,Otaciro R.The existence of a mucilaginous envelope, sheath or capsule is usual in many desmids, but few data concerning its function are available. Previous studies of the transport function and permeation of molecules through the algae capsules were done using the algae Spondylosium panduriforme and Nephrocytium lunatum, the Electron Paramagnetic Resonance (EPR) technique, and different spin labels. The results suggeste...
Dimensionamento simplificado de uma linha de distribuição eléctrica em corrente...
Vieira,ArmandoNeste trabalho é calculada a tensão e resistência equivalente ao longo de uma linha eléctrica em corrente contínua alimentando N cargas equidistantes. É obtida uma expressão simples recorrendo à aproximação de linha contínua e considerando a resistência do fio pequena quando comparada com as cargas.
Estimating Bankruptcy Using Neural Networks Trained with Hidden Layer Learning ...
Neves, João Carvalho das; Vieira, ArmandoThe Hidden Layer Learning Vector Quantization (HLVQ), a recent algorithm for training neural networks, is used to correct the output of traditional MultiLayer Preceptrons (MLP) in estimating the probability of company bankruptcy. It is shown that this method improves the results of traditional neural networks and outperforms substantially the discriminant analysis in predicting one-year advance bankruptcy. We a...
A training algorithm for classification of high-dimensional data
Vieira, Armando; Barradas, NunoWe propose an algorithm for training multi layer preceptrons (MLP) for classification problems, that we named hidden layer learning vector quantization. It consists of applying learning vector quantization to the last hidden layer of a MLP and it gave very successful results on problems containing a large number of correlated inputs. It was applied with excellent results on classification of Rutherford backscat...
Comparison of the spherically averaged pseudopotential model with the stabilize...
Vieira, Armando; Begoña Torres, M.; Fiolhais, Carlos; Carlos Balbás, L.We compare Kohn - Sham results (density, cohesive energy, size and effect of charging) of the spherically averaged pseudopotential model with the stabilized jellium model for clusters of sodium and aluminium with less than 20 atoms. We find that the stabilized jellium model, although conceptually and practically simpler, gives better results for the cohesive energy and the elastic stiffness. We use the local de...
Fission of metallic clusters in the liquid drop model
Vieira, Armando; Fiolhais, CarlosUsing the liquid drop model and the jellium model, we calculate fission barrier heights as a function of charge and mass asymmetry for a family of shapes consisting of two spheres connected by a quadratic surface. We find the fissibility for which a mass asymmetric splitting gives place to the symmetric one (Bussinaro-Gallone point) and evaluate the size of charged clusters of alkali metals for which the fissio...
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