Algoritmo modificado de PSO matricial aplicado a identificação de sistemas com análise de convergência

Recentemente diversas técnicas de computação evolucionárias têm sido utilizadas em áreas como estimação de parâmetros de processos dinâmicos lineares e não lineares ou até sujeitos a incertezas. Isso motiva a utilização de algoritmos como o otimizador por nuvem de partículas (PSO) nas referidas áreas do conhecimento. Porém, pouco se sabe sobre a convergência desse algoritmo e, principalmente, as análises e estudos realizados têm se concentrado em resultados experimentais. Por isso, é objetivo deste trabalho propor uma nova estrutura para o PSO que permita analisar melhor a convergência do algoritmo de forma analítica. Para isso, o PSO é reestruturado para assumir uma forma matricial e reformulado como um sistema linear por partes. As partes serão analisadas de forma separada e será proposta a inserção de um fator de esquecimento que garante que a parte mais significativa deste sistema possua autovalores dentro do círculo de raio unitário. Também será realizada a análise da convergência do algoritmo como um todo, utilizando um critério de convergência quase certa, aplicável a sistemas chaveados. Na sequência, serão realizados testes experimentais de maneira a verificar o comportamento dos autovalores após a inserção do fator de esquecimento. Posteriormente, os algoritmos de identificação de parâmetros tradicionais serão combinados com o PSO matricial, de maneira a tornar os resultados da identificação tão bons ou melhores que a identificação apenas com o PSO ou, apenas com os algoritmos tradicionais. Os resultados mostram a convergência das partículas em uma região delimitada e que as funções obtidas após a combinação do algoritmo PSO matricial com os algoritmos convencionais, apresentam maior generalização para o sistema apresentado. As conclusões a que se chega é que a hibridização, apesar de limitar a busca por uma partícula mais apta do PSO, permite um desempenho mínimo para o algoritmo e ainda possibilita melhorar o resultado obtido com os algoritmos tradicionais, permitindo a representação do sistema aproximado em quantidades maiores de frequências.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

Escala diagramática e influência de sistemas de produção na ocorrência do crestamento gomoso da melancia

CHAPTER 1 - The gummy stem blight, caused by the fungus D. bryoniae, is a disease commonly found in watermelon cultivated in several countries. In Brazil, there are numerous studies related to the disease, but there are not uniform methods for quantifying of disease severity in the field. Thus, we developed a diagrammatic scale based on scanned photos of watermelon leaves infected with D. bryoniae. The scale developed showed levels of 0; 10; 20; 45; 65 and 90% of severity. The scale validation was divided into two parts: initially, 10 evaluators (half with experienced and other half without experience) estimated the disease severity based on the initial observation of 100 photos of watermelon leaves with symptoms of the disease at different severity levels. Before, the same evaluators estimated the disease severity with the support of the scale prepared from the Quant program. Data were analyzed using linear regression and were obtained angular, linear, and correlation coefficients. Based on these data, we determined the accuracy and precision of the evaluations. The correlation coefficients (R2) ranged from 0.88 - 0.97 for the experienced evaluators and from 0.55 - 0.95 for the inexperienced evaluators. The average angular coefficient (A) for inexperienced evaluators was 20.42 and 8.61 with and without the support of diagrammatic scale, respectively. Experienced evaluators showed values of average linear coefficient of 5.30 and 1.68 with and without the support of diagrammatic scale, respectively. The absolute errors analysis indicated that the use of diagrammatic scale contributed to minimize the flaws in the severity levels estimation. The diagrammatic scale proposed shown adequate for gummy stem blight severity evaluation in watermelon. CHAPTER 2 - The gummy stem blight (Didymella bryoniae) is a disease that affects the productivity of watermelon leading to losses over 40%. This study aimed to evaluate the efficiency of different production systems in control of gummy stem blight in watermelon for to establish efficient methods to combat the disease. There were applied the following treatments: conventional tillage (T1), integrated management (T2) and organic management (T3). In T1 and T2 were applied mineral fertilization and T3 was used bovine manure. There was application of fungicides and insecticides in commercial dose in T1 and T2, being after soil chemical analysis in T2. Disease severity was assessed by grading scale. The experimental design was randomized blocks. The severity of gummy stem blight has increased substantially during the fruit formation. Watermelon plants grown with integrated management (T2) showed lower levels of disease severity, while plants in organic management (T3) exhibited higher levels of severity. We conclude that management based on judicious accompaniments in field represents best way to achieve the phytosanitary aspect adequate for cultivation of watermelon in Tocantins.

Modelo para distribuição de recursos nos municípios brasileiros baseado na lei de diretrizes orçamentárias, análise multicritério e programação linear

The municipal management in any country of the globe requires planning and allocation of resources evenly. In Brazil, the Law of Budgetary Guidelines (LDO) guides municipal managers toward that balance. This research develops a model that seeks to find the balance of the allocation of public resources in Brazilian municipalities, considering the LDO as a parameter. For this using statistical techniques and multicriteria analysis as a first step in order to define allocation strategies, based on the technical aspects arising from the municipal manager. In a second step, presented in linear programming based optimization where the objective function is derived from the preference of the results of the manager and his staff. The statistical representation is presented to support multicriteria development in the definition of replacement rates through time series. The multicriteria analysis was structured by defining the criteria, alternatives and the application of UTASTAR methods to calculate replacement rates. After these initial settings, an application of linear programming was developed to find the optimal allocation of enforcement resources of the municipal budget. Data from the budget of a municipality in southwestern Paraná were studied in the application of the model and analysis of results.

Nuevo método de identificación usando la respuesta escalón para sistemas de fase no mínima de segundo orden

Este artículo presenta un nuevo método de identificación para sistemas de fase no mínima basado en la respuesta escalón. El enfoque propuesto provee un modelo aproximado de segundo orden evitando diseños experimentales complejos. El método propuesto es un algoritmo de identificación cerrado basado en puntos característicos de la respuesta escalón de sistemas de fase no mínima de segundo orden. Él es validado usando diferentes modelos lineales. Ellos tienen respuesta inversa entre 3,5% y 38% de la respuesta en régimen permanente. En simulaciones, ha sido demostrado que resultados satisfactorios pueden ser obtenidos usando el procedimiento de identificación propuesto, donde los parámetros identificados presentan errores relativos medios, menores que los obtenidos mediante el método de Balaguer.

Formulação lagrangiana para sistemas dissipativos através do cálculo fracionário

Neste trabalho, generalizamos o Princípio da Mínima Ação proposto por Riewe para sistemas não conservativos, contendo forças dissipativas lineares dependentes de derivadas temporais de qualquer ordem. A Ação generalizada é construída a partir de funções Lagrangianas dependentes de derivadas de ordem inteira e fracionária. Diferente de outras formulações, o uso de derivadas fracionárias permite a construção de Lagrangianas físicas para sistemas não conservativos. Uma Lagrangiana é dita física se fornece relações fisicamente consistentes para o momentum e o Hamiltoniano do sistema. Neste Princípio da Mínima Ação generalizado, as equações de movimento são obtidas a partir da equação de Euler-Lagrange e, tomando-se o limite indo à zero para o intervalo de tempo definindo a Ação. Finalmente, como exemplo de aplicação, formulamos pela primeira vez uma Lagrangiana física para o problema da carga pontual acelerada.

Controle de sistema não linear de separação gás/líquido sob ação de efeitos transientes fluídicos por sliding control

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2015.

Análise estequiométrica da dinâmica não-linear de redes de reações químicas

Dissertação (mestrado)—Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2016.

Perpectiva linear paramétrica

Tese de Doutoramento em Arquitetura, com a especialização em Comunicação Visual, apresentada na Faculdade de Arquitetura da Universidade de Lisboa, para obtenção do grau de Doutor.

Aspectos de uma transição : a reconstrução do Direito Civil para um Direito Civil-Constitucional à luz da teoria dos sistemas, da tópica e da dignidade da pessoa humana

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Direito, Programa de Pós-Graduação em Direito, 2016.

Análise não linear de séries temporais e aplicações à Psicologia

Nesta dissertação estudámos as séries temporais que representam a complexa dinâmica do comportamento. Demos especial atenção às técnicas de dinâmica não linear. As técnicas fornecem-nos uma quantidade de índices quantitativos que servem para descrever as propriedades dinâmicas do sistema. Estes índices têm sido intensivamente usados nos últimos anos em aplicações práticas em Psicologia. Estudámos alguns conceitos básicos de dinâmica não linear, as características dos sistemas caóticos e algumas grandezas que caracterizam os sistemas dinâmicos, que incluem a dimensão fractal, que indica a complexidade de informação contida na série temporal, os expoentes de Lyapunov, que indicam a taxa com que pontos arbitrariamente próximos no espaço de fases da representação do espaço dinâmico, divergem ao longo do tempo, ou a entropia aproximada, que mede o grau de imprevisibilidade de uma série temporal. Esta informação pode então ser usada para compreender, e possivelmente prever, o comportamento. ABSTRACT: ln this thesis we studied the time series that represent the complex dynamic behavior. We focused on techniques of nonlinear dynamics. The techniques provide us a number of quantitative indices used to describe the dynamic properties of the system. These indices have been extensively used in recent years in practical applications in psychology. We studied some basic concepts of nonlinear dynamics, the characteristics of chaotic systems and some quantities that characterize the dynamic systems, including fractal dimension, indicating the complexity of information in the series, the Lyapunov exponents, which indicate the rate at that arbitrarily dose points in phase space representation of a dynamic, vary over time, or the approximate entropy, which measures the degree of unpredictability of a series. This information can then be used to understand and possibly predict the behavior.

Effect Of Simulated Microwave Disinfection On The Linear Dimensional Change, Hardness And Impact Strength Of Acrylic Resins Processed By Different Polymerizing Cycles.

This study investigated the effect of simulated microwave disinfection (SMD) on the linear dimensional changes, hardness and impact strength of acrylic resins under different polymerization cycles. Metal dies with referential points were embedded in flasks with dental stone. Samples of Classico and Vipi acrylic resins were made following the manufacturers' recommendations. The assessed polymerization cycles were: A-- water bath at 74ºC for 9 h; B-- water bath at 74ºC for 8 h and temperature increased to 100ºC for 1 h; C-- water bath at 74ºC for 2 h and temperature increased to 100ºC for 1 h;; and D-- water bath at 120ºC and pressure of 60 pounds. Linear dimensional distances in length and width were measured after SMD and water storage at 37ºC for 7 and 30 days using an optical microscope. SMD was carried out with the samples immersed in 150 mL of water in an oven (650 W for 3 min). A load of 25 gf for 10 sec was used in the hardness test. Charpy impact test was performed with 40 kpcm. Data were submitted to ANOVA and Tukey's test (5%). The Classico resin was dimensionally steady in length in the A and D cycles for all periods, while the Vipi resin was steady in the A, B and C cycles for all periods. The Classico resin was dimensionally steady in width in the C and D cycles for all periods, and the Vipi resin was steady in all cycles and periods. The hardness values for Classico resin were steady in all cycles and periods, while the Vipi resin was steady only in the C cycle for all periods. Impact strength values for Classico resin were steady in the A, C and D cycles for all periods, while Vipi resin was steady in all cycles and periods. SMD promoted different effects on the linear dimensional changes, hardness and impact strength of acrylic resins submitted to different polymerization cycles when after SMD and water storage were considered.

Effect Of Simulated Microwave Disinfection On The Linear Dimensional Change, Hardness And Impact Strength Of Acrylic Resins Processed By Different Polymerization Cycles.

This study investigated the effect of simulated microwave disinfection (SMD) on the linear dimensional changes, hardness and impact strength of acrylic resins under different polymerization cycles. Metal dies with referential points were embedded in flasks with dental stone. Samples of Classico and Vipi acrylic resins were made following the manufacturers' recommendations. The assessed polymerization cycles were: A) water bath at 74 ºC for 9 h; B) water bath at 74 ºC for 8 h and temperature increased to 100 ºC for 1 h; C) water bath at 74 ºC for 2 h and temperature increased to 100 ºC for 1 h; and D) water bath at 120 ºC and pressure of 60 pounds. Linear dimensional distances in length and width were measured after SMD and water storage at 37 ºC for 7 and 30 days using an optical microscope. SMD was carried out with the samples immersed in 150 mL of water in an oven (650 W for 3 min). A load of 25 gf for 10 s was used in the hardness test. Charpy impact test was performed with 40 kpcm. Data were submitted to ANOVA and Tukey's test (5%). The Classico resin was dimensionally steady in length in the A and D cycles for all periods, while the Vipi resin was steady in the A, B and C cycles for all periods. The Classico resin was dimensionally steady in width in the C and D cycles for all periods, and the Vipi resin was steady in all cycles and periods. The hardness values for Classico resin were steady in all cycles and periods, while the Vipi resin was steady only in the C cycle for all periods. Impact strength values for Classico resin were steady in the A, C and D cycles for all periods, while Vipi resin was steady in all cycles and periods. SMD promoted different effects on the linear dimensional changes, hardness and impact strength of acrylic resins submitted to different polymerization cycles when after SMD and water storage were considered.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Homogeneidade e heterogeneidade nos sistemas educacionais: Argentina, Brasil, Chile e México

This study focus on the reconfiguration of educational management in Argentina, Brazil, Chile and Mexico, which was promoted by the new logic of social regulation and the new role attributed to the State, considering each country's own historicity. So, the cultural factors that interfere on the dynamics of the 90' school reform are analyzed. Aspects that show the homogeneity or heterogeneity of these reforms in the region, as well as local specificities that block out the concretization of the reform are underlined. It is shown that the historicity that characterizes the educational reform has taken, in each country, a form that can be called, in Mexico, conservative rupture; in Chile, conservative continuity; in Brazil, conservative renovation; and, in Argentina, interrupted rupture. Some conclusions about the impact of educational reform in the selected countries are recuperated through the analysis of 186 academic texts on the subject.