Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Sistema inteligente para previsão de carga multinodal em sistemas elétricos de potência

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Proposta de implementação de redes de base radial em tecnologias CMOS e BiCMOS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative study between RBF and radial-PPS neural networks

The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

Aprendizado não-supervisionado em redes neurais pulsadas de base radial: um estudo da capacidade de agrupamento para a classificação de pixels

Redes neurais pulsadas - redes que utilizam uma codificação temporal da informação - têm despontado como uma promissora abordagem dentro do paradigma conexionista, emergente da ciência cognitiva. Um desses novos modelos é a rede neural pulsada com função de base radial, que é capaz de armazenar informação nos tempos de atraso axonais dos neurônios. Um algoritmo de aprendizado foi aplicado com sucesso nesta rede pulsada, que se mostrou capaz de mapear uma seqüência de pulsos de entrada em uma seqüência de pulsos de saída. Mais recentemente, um método baseado no uso de campos receptivos gaussianos foi proposto para codificar dados constantes em uma seqüência de pulsos temporais. Este método tornou possível a essa rede lidar com dados computacionais. O processo de aprendizado desta nova rede não se encontra plenamente compreendido e investigações mais profundas são necessárias para situar este modelo dentro do contexto do aprendizado de máquinas e também para estabelecer as habilidades e limitações desta rede. Este trabalho apresenta uma investigação desse novo classificador e um estudo de sua capacidade de agrupar dados em três dimensões, particularmente procurando estabelecer seus domínios de aplicação e horizontes no campo da visão computacional.

Analytical functions for the calculation of hyperspherical potential curves of atomic systems

We present angular basis functions for the Schrödinger equation of two-electron systems in hyperspherical coordinates. By using the hyperspherical adiabatic approach, the wave functions of two-electron systems are expanded in analytical functions, which generalizes the Jacobi polynomials. We show that these functions, obtained by selecting the diagonal terms of the angular equation, allow efficient diagonalization of the Hamiltonian for all values of the hyperspherical radius. The method is applied to the determination of the 1S e energy levels of the Li + and we show that the precision can be improved in a systematic and controllable way. ©2000 The American Physical Society.

Treinamento de uma rede neural de base radial usando computação evolutiva: implementação e aplicações

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

EEG signal classification for epilepsy diagnosis via optimum path forest - A systematic assessment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo da adsorção de hidrogênio e sulfeto na superfície de paládio: aspectos experimentais (eletroquímica) e teóricos (ab initio e Teoria do Funcional da Densidade)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Monte Carlo investigations of intermolecular interactions in water-amide mixtures

Monte Carlo simulations of water-amides (amide=fonnamide-FOR, methylfonnamide-NMF and dimethylformamide-DMF) solutions have been carried out in the NpT ensemble at 308 K and 1 atm. The structure and excess enthalpy of the mixtures as a function of the composition have been investigated. The TIP4P model was used for simulating water and six-site models previously optimized in this laboratory were used for simulating the liquid amides. The intermolecular interaction energy was calculated using the classical 6-12 Lennard-Jones potential plus a Coulomb term. The interaction energy between solute and solvent has been partitioned what leads to a better understanding of the behavior of the enthalpy of mixture obtained for the three solutions experimentally. Radial distribution functions for the water-amides correlations permit to explore the intermolecular interactions between the molecules. The results show that three, two and one hydrogen bonds between the water and the amide molecules are formed in the FOR, NMF and DMF-water solutions, respectively. These H-bonds are, respectively, stronger for DMF-water, NMF-water and FOR-water. In the NMF-water solution, the interaction between the methyl group of the NMF and the oxygen of the water plays a role in the stabilization of the aqueous solution quite similar to that of an H-bond in the FOR-water solution. (c) 2005 Elsevier B.V. All rights reserved.

Monte Carlo thermodynamic and structural properties of the TIP4P water model: dependence on the computational conditions

Classical Monte Carlo simulations were carried out on the NPT ensemble at 25°C and 1 atm, aiming to investigate the ability of the TIP4P water model [Jorgensen, Chandrasekhar, Madura, Impey and Klein; J. Chem. Phys., 79 (1983) 926] to reproduce the newest structural picture of liquid water. The results were compared with recent neutron diffraction data [Soper; Bruni and Ricci; J. Chem. Phys., 106 (1997) 247]. The influence of the computational conditions on the thermodynamic and structural results obtained with this model was also analyzed. The findings were compared with the original ones from Jorgensen et al [above-cited reference plus Mol. Phys., 56 (1985) 1381]. It is notice that the thermodynamic results are dependent on the boundary conditions used, whereas the usual radial distribution functions g(O/O(r)) and g(O/H(r)) do not depend on them.

Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)