Caracterização, simulação (à escala) e modelação do escoamento em canais artificiais: aplicação a caso de estudo

Os escoamentos no interior de zonas urbanas, apresentam grande heterogeneidade, pelo que a sua caracterização, requer uma formulação que incorpore explicitamente essa variabilidade espacial. A caracterização, simulação (à escala) e modelação do escoamento em canais artificiais e a aplicação a um caso de estudo, no Laboratório de Hidráulica da UMa, representa o cerne desta dissertação. Os objetivos principais desta dissertação são: a caracterização e desenvolvimento de ferramentas de simulação do comportamento do escoamento em canais artificiais, no caso de uma variação súbita dos caudais afluentes, mecanismos de prevenção de cheia; o desenvolvimento de um modelo de simulação hidrodinâmico, considerando os escoamentos variáveis em superfície livre no caso de situações de cheia, na simulação entre as condições variáveis das afluências, das condições hidromorfológicas do canal e da instalação e operação dos sistemas e regulação dos escoamentos; e ainda a análise da viabilidade da simulação (modelo) na gestão e prevenção de cheias em canais artificiais. Numa primeira instância, procede-se à recolha de toda a informação bibliográfica disponível. Com recurso aos modelos digitais do terreno e ao programa ArcGis, é efetuada toda uma exaustiva caracterização da bacia hidrográfica, relativa ao caso de estudo (canal artificial), a partir da qual foi possível obter os dados inerentes às características geométricas, características de relevo e características de drenagem. Segue-se a análise da precipitação com recurso a folhas de cálculo e dados fornecidos pelas instituições pertinentes, de forma a obter valores de precipitação média diária e anual para aplicação de fórmulas, tanto para calcular valores de tempo de concentração, bem como caudais. O próximo passo é selecionar os troços relevantes do canal em estudo e com recurso ao equipamento disponível no Laboratório de Hidráulica da UMa, à folha de cálculo programada e ao programa HEC-RAS procede-se à simulação/modelação/análise desses troços, comparando o resultado/comportamento simulado, com o expectável e entre os vários métodos. Por fim, são expostas as conclusões, bem como algumas considerações finais e uma listagem de objetivos a manter ou alcançar nos próximos anos, onde se incluem, ações prioritárias e recomendações visando, não só melhorar o processo de caracterização do escoamento em canais artificiais, bem como simplificar a prevenção e gestão de cheias.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Características limnológicas e estrutura trófica das comunidades de peixes de alguns lagos naturais e artificiais do Rio Grande do Norte

Artificial lakes must differ from natural lakes in important structural and functional aspects that need to be understood so that these ecosystems can be properly managed. The aim of this work was to test the hypothesis that the artificial lakes (impoundments) in the semi-arid region of the Rio Grande do Norte State are more eutrophic and turbid and have different trophic structure when compared to the natural coastal lakes that occur in the humid eastern coast of the State. To test this hypothesis, 10 natural lakes and 8 artificial lakes with about 100 ha were sampled between September and November 2005 for the determination of some limnological variables and the abundance of the main fish species, which were grouped in three trophic guilds: facultative piscivores, facultative planktivores and omnivores. The results show that the artificial lakes had significantly higher concentrations of total nitrogen, total phosphorus, chlorophyll a , total and volatile suspended solids than the natural lakes. Results also show that the values of pH, total alkalinity, electric conductivity, turbidity as well as the coefficient of vertical attenuation of light were significantly higher in the artificial lakes than in the natural lakes. In the artificial lakes, the abundance of facultative planktivores was significantly higher, while the abundance of facultative piscivores significantly lower than in the natural lakes. There was no significant difference in the abundance of omnivorous fish between the two types of lakes. These results suggest that the increase in turbidity together with the other changes in the water quality of the artificial lakes, modifies the trophic structure of the fish communities reducing the importance of piscivores and the length of the food chains

Um sistema para a inferência de variáveis usando redes neurais artificiais

This work aims to obtain a low-cost virtual sensor to estimate the quality of LPG. For the acquisition of data from a distillation tower, software HYSYS ® was used to simulate chemical processes. These data will be used for training and validation of an Artificial Neural Network (ANN). This network will aim to estimate from available simulated variables such as temperature, pressure and discharge flow of a distillation tower, the mole fraction of pentane present in LPG. Thus, allowing a better control of product quality

Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Efeito do consórcio de milho com Panicum maximum na comunidade infestante e na cultura da soja em rotação

Objetivou-se com este trabalho estudar os efeitos do consórcio de milho com colonião (Panicum maximum cv. Aruana) na infestação de plantas daninhas e na cultura da soja em rotação. O experimento foi realizado em campo, no período de dezembro de 2008 a abril de 2010, em área experimental da UNESP, campus de Jaboticabal-SP. Utilizou-se o delineamento em blocos ao acaso, com quatro repetições, em esquema de parcela subdividida. Foram estudadas duas formas de semeadura (a lanço e em linha) de colonião nas parcelas e quatro quantidades de sementes (200, 400, 600 e 800 pontos de valor cultural - PVC) nas subparcelas, além de três testemunhas, representadas pelo monocultivo das espécies, como tratamentos adicionais. O cultivo consorciado não afetou o desenvolvimento do milho, comparado ao milho solteiro. Embora na colheita do milho houvesse maior matéria seca e densidade de plantas de colonião com a semeadura de 800 PVC, antes da semeadura da soja o acúmulo de massa não diferiu entre os tratamentos de consórcio. Portanto, a semeadura de 200 PVC de sementes de colonião, a lanço ou em linha, foi suficiente para a manutenção de quantidade (9,1 t ha-1) adequada de palha sobre o solo. Antecedendo a semeadura da soja, a infestação de plantas daninhas na testemunha de milho solteiro foi maior do que nos tratamentos de consórcio e nas testemunhas da forrageira solteira (a lanço e em linha). O mesmo foi observado para densidade de plantas daninhas após a instalação da cultura. Os sistemas de consórcio de milho com colonião não interferiram em nenhuma característica avaliada na cultura da soja cultivada em rotação. da mesma forma, não foi observada diferença entre os tratamentos de consórcios e a testemunha de milho em monocultivo para produção de grãos de soja.

Dietas artificiais incorporadas ou não a colmos triturados de variedades de cana-de-açúcar na biologia de Diatraea saccharalis (F.) (Lepidoptera: Crambidae)

It was studied the incorporation or not of shredded stems of sugarcane varieties to artificial diets and their effect in the biology of Diatraea saccharalis (Fabr., 1794) (Lepidoptera: Crambidae) under laboratory conditions. The experiment was carried out at the Department of Plant Protection of FCAV-UNESP, Jaboticabal, São Paulo, Brazil, in 2007, using diets with different amounts of their components (100, 75, 25 e 25% of concentration of the standard diet). The experiment had a complete randomized design in a 4x3 factorial scheme, using 4 concentrations of diets and three treatments, in a total of 12, with 6 replications. The larval, pupal an total periods and viability were evaluated, as well as the larval weight at 15 days, the pupal weight after 24 hours and the longevity of adults without feeding. The diet with 25% concentration of the components compared to the standard diet had a negative effect in the development of D. saccharlis larvae. Shredded dry stalks incorporated or not to the diet affected only the larval and pupal weight whereas the larval weight was more affected when the resistant (RB83-5486) and susceptible (SP80-3280) varieties due to the use of diet with 50% of its components. The diet with 100% concentration of its components are more favorable to the development of D. saccharalis, with 25% while that is less favorable. The diet with 100% concentration of the components associated with the presence of SP80-3280 (susceptible) stem variety provides greater larval weight. The weights of larvae and pupae of insects are negatively affected when RB83-5486 (resistant) shredded dry stem variety is incorporated into the diet. regarding to larval weight the diet with 50% of the concentration of its components provides better discrimination between genotypes resistant and susceptible to sugarcane borer.