Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Short-term planning of electric power distribution networks using multiobjective genetic algorithim

The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.

Alocação de Chaves para Transferências Automáticas de Cargas entre Subestações Utilizando Algoritmo Busca Tabu Reativa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metaheurística particle swarm utilizada para alocação ótima de bancos de capacitores em sistemas de distribuição radial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Imageamento da porosidade através de perfis geofísicos de poço

O imageamento da porosidade é uma representação gráfica da distribuição lateral da porosidade da rocha, estimada a partir de dados de perfis geofísicos de poço. Apresenta-se aqui uma metodologia para produzir esta imagem geológica, totalmente independente da intervenção do intérprete, através de um algoritmo, dito, interpretativo baseado em dois tipos de redes neurais artificiais. A primeira parte do algoritmo baseia-se em uma rede neural com camada competitiva e é construído para realizar uma interpretação automática do clássico gráfico o P_b - Φ_N, produzindo um zoneamento do perfil e a estimativa da porosidade. A segunda parte baseia-se em uma rede neural com função de base radial, projetado para realizar uma integração espacial dos dados, a qual pode ser dividida em duas etapas. A primeira etapa refere-se à correlação de perfis de poço e a segunda à produção de uma estimativa da distribuição lateral da porosidade. Esta metodologia ajudará o intérprete na definição do modelo geológico do reservatório e, talvez o mais importante, o ajudará a desenvolver de um modo mais eficiente as estratégias para o desenvolvimento dos campos de óleo e gás. Os resultados ou as imagens da porosidade são bastante similares às seções geológicas convencionais, especialmente em um ambiente deposicional simples dominado por clásticos, onde um mapa de cores, escalonado em unidades de porosidade aparente para as argilas e efetiva para os arenitos, mostra a variação da porosidade e a disposição geométrica das camadas geológicas ao longo da seção. Esta metodologia é aplicada em dados reais da Formação Lagunillas, na Bacia do Lago Maracaibo, Venezuela.

A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A mixed-integer quadratically-constrained programming model for the distribution system expansion planning

This paper presents a mixed-integer quadratically-constrained programming (MIQCP) model to solve the distribution system expansion planning (DSEP) problem. The DSEP model considers the construction/reinforcement of substations, the construction/reconductoring of circuits, the allocation of fixed capacitors banks and the radial topology modification. As the DSEP problem is a very complex mixed-integer non-linear programming problem, it is convenient to reformulate it like a MIQCP problem; it is demonstrated that the proposed formulation represents the steady-state operation of a radial distribution system. The proposed MIQCP model is a convex formulation, which allows to find the optimal solution using optimization solvers. Test systems of 23 and 54 nodes and one real distribution system of 136 nodes were used to show the efficiency of the proposed model in comparison with other DSEP models available in the specialized literature. (C) 2014 Elsevier Ltd. All rights reserved.

Alocação de bancos de capacitores em sistemas de distribuição radiais usando busca dispersa

Pós-graduação em Engenharia Elétrica - FEIS

Heurística especializada aplicada na alocação ótima de bancos de capacitores em sistemas de distribuição radial

Pós-graduação em Engenharia Elétrica - FEIS

Monte Carlo simulation of water-tetrahydrofuran mixtures

Monte Carlo simulations of water-tetrahydrofuran (THF) mixtures were performed in the isothermal-isobaric ensemble (NPT) at T = 298 K and p = 1 atm. The interaction energy was calculated using the TIP4P model for water and a five-site united atom representation for the THF molecule. The potential energy surfaces for water-THF interactions were obtained by using combining rules and the original potential functions used for pure liquids. Theoretical values obtained for the average interaction energy as a function of concentration are in good agreement with available experimental data. Results from the partitioning of the total interaction energy into water-water, water-THF and THF-THF contributions are presented. These results are useful to distinguish between the quantitative contributions of these molecular interactions to the energetic behavior of the water-THF mixing process. The radial distribution functions for HW-OTHF and OW-OTHF site-site interactions show the salient features of hydrogen-bonded liquids. Comparison of the average number of water-water complexes interacting through hydrogen bonding in water-THF and water-methanol mixtures shows an enhancement of the water-water coordination number in a THF rich environment. © 1995.

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

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

The Truncated Inflated Beta Distribution

The study of proportions is a common topic in many fields of study. The standard beta distribution or the inflated beta distribution may be a reasonable choice to fit a proportion in most situations. However, they do not fit well variables that do not assume values in the open interval (0, c), 0 < c < 1. For these variables, the authors introduce the truncated inflated beta distribution (TBEINF). This proposed distribution is a mixture of the beta distribution bounded in the open interval (c, 1) and the trinomial distribution. The authors present the moments of the distribution, its scoring vector, and Fisher information matrix, and discuss estimation of its parameters. The properties of the suggested estimators are studied using Monte Carlo simulation. In addition, the authors present an application of the TBEINF distribution for unemployment insurance data.

Polyelectrolytes and their counterions studied by EPR spectroscopy

In this thesis methods of EPR spectroscopy were used to investigate polyion-counterion interactions in polyelectrolyte solutions. The fact that EPR techniques are local methods is exploited and by employing spin-carrying (i.e., EPR-active) probe ions it is possible to examine polyelectrolytes from the counterions’ point of view. It was possible to gain insight into i) the dynamics and local geometry of counterion attachment, ii) conformations and dynamics of local segments of the polyion in an indirect manner, and iii) the spatial distribution of spin probe ions that surround polyions in solution. Analysis of CW EPR spectra of dianion nitroxide spin probe Fremy’s salt (FS, potassium nitrosodisulfonate) in solutions of cationic PDADMAC polyelectrolyte revealed that FS ions and PDADMAC form transient ion pairs with a lifetime of less than 1 ns. This effect was termed as dynamic electrostatic attachment (DEA). By spectral simulation taking into account the rotational dynamics as a uniaxial Brownian reorientation, also the geometry of the attached state could be characterized. By variation of solvent, the effect of solvent viscosity and permittivity were investigated and indirect information of the polyelectrolyte chain motion was obtained. Furthermore, analysis of CW EPR data also indicates that in mixtures of organic solvent/water PDADMAC chains are preferentially solvated by the organic solvent molecules, while in purely aqueous mixtures the PDADMAC chain segments were found in different conformations depending on the concentration ratio R of FS counterions to PDADMAC repeat units.Broadenings in CW EPR spectra of FS ions were assigned to spin-exchange interaction and hence contain information on the local concentrations and distributions of the counterions. From analysis of these broadenings in terms of a modified cylindrical cell approach of polyelectrolyte theory, radial distribution functions for the FS ions in the different solvents were obtained. This approach breaks down in water above a threshold value of R, which again indicates that PDADMAC chain conformations are altered as a function of R. Double electron-electron resonance (DEER) measurements of FS ions were carried out to probe the distribution of attached counterions along polyelectrolyte chains. For a significant fraction of FS spin probes in solution with a rigid-rod model polyelectrolyte containing charged Ru2+-centers, a bimodal distance distribution was found that nicely reproduced the spacings of direct and next-neighbor Ru2+-centers along the polyelectrolyte: 2.35 and 4.7 nm. For the system of FS/PDADMAC, DEER data could be simulated by assuming a two-state distribution of spin probes, one state corresponding to a homogeneous (3-dimensional) distribution of spin probes in the polyelectrolyte bulk and the other to a linear (1-dimensional) distribution of spin probes that are electrostatically condensed along locally extended PDADMAC chain segments. From this analysis it is suggested that the PDADMAC chains form locally elongated structures of a size of at least ~5 nm.

On the Luminous and Dark Matter Distribution in Early-Type Galaxies

The way mass is distributed in galaxies plays a major role in shaping their evolution across cosmic time. The galaxy's total mass is usually determined by tracing the motion of stars in its potential, which can be probed observationally by measuring stellar spectra at different distances from the galactic centre, whose kinematics is used to constrain dynamical models. A class of such models, commonly used to accurately determine the distribution of luminous and dark matter in galaxies, is that of equilibrium models. In this Thesis, a novel approach to the design of equilibrium dynamical models, in which the distribution function is an analytic function of the action integrals, is presented. Axisymmetric and rotating models are used to explain observations of a sample of nearby early-type galaxies in the Calar Alto Legacy Integral Field Area survey. Photometric and spectroscopic data for round and flattened galaxies are well fitted by the models, which are then used to get the galaxies' total mass distribution and orbital anisotropy. The time evolution of massive early-type galaxies is also investigated with numerical models. Their structural properties (mass, size, velocity dispersion) are observed to evolve, on average, with redshift. In particular, they appear to be significantly more compact at higher redshift, at fixed stellar mass, so it is interesting to investigate what drives such evolution. This Thesis focuses on the role played by dark-matter haloes: their mass-size and mass-velocity dispersion correlations evolve similarly to the analogous correlations of ellipticals; at fixed halo mass, the haloes are more compact at higher redshift, similarly to massive galaxies; a simple model, in which all the galaxy's size and velocity-dispersion evolution is due to the cosmological evolution of the underlying halo population, reproduces the observed size and velocity-dispersion of massive compact early-type galaxies up to redshift of about 2.