Interferência do método de previsão populacional no desempenho hidráulico de uma rede coletora de esgoto sanitário

The non existence of sewage services creates an unhealthy environmental, causing impact extremely prejudicial to the human health. In Brazil, this item represents the biggest deficit in the basic sanitation these days, and only about 50% of the population is attended. The sewage collection network is a needful system for the basic sanitation. Between the parameters of the project of a system of collection and sewage transportation, the definition of the population that will be attended is one of the most important variables, and that should be done based on criterion of population growth and in accordant to directrix presents in the comprehensive city plan. In this paper, were evaluated methods of growth based on the geometric growth rate, on the population density and on the number of residents per dwelling, and also mathematics models of growth prediction, emphasizing in the geometric growth and on the logistic curve method. That way, the goal of this paper were value the hydraulic performance in one of the watersheds delimited by the sewage network magnification work existent in the city of Cacoal–RO. Using simulation with different scenarios, the results pointed that the hydraulic performance of the system were strongly affected by the population determination method used. For the same drained area the diameters range from 150 to 250 mm as well as the trench’s deep, where some stretches exceeded the maximum values contained in the standard. Besides, the variation of the sewage contribution rate due the population variation estimated in different scenarios, led to alterations in others important project parameters, such as slope, shallow pool, tensile stress and spreading velocity

Previsão de vendas para uma indústria de equipamentos pesados: seleção de técnicas e análise

The continuous advance of the Brazilian economy and increased competition in the heavy equipment market, increasingly point to the need for accurate sales forecasting processes, which allow an optimized strategic planning and therefore better overall results. In this manner, we found that the sales forecasting process deserves to be studied and understood, since it has a key role in corporate strategic planning. Accurate forecasting methods enable direction of companies to circumvent the management difficulties and the variations of finished goods inventory, which make companies more competitive. By analyzing the stages of the sales forecasting it was possible to observe that this process is methodical, bureaucratic and demands a lot of training for their managers and professionals. In this paper we applied the modeling method and the selecting process which has been done for Armstrong to select the most appropriate technique for two products of a heavy equipment industry and it has been through this method that the triple exponential smoothing technique has been chosen for both products. The results obtained by prediction with the triple exponential smoothing technique were better than forecasts prepared by the industry experts

Previsão da demanda doméstica da aviação comercial européia

This paper work has as objective the study and forecasting of the demand behavior for the European commercial aviation industry. Once economy and demand has a straight relationship, the tool chosen to perform this forecast was the Econometry. In order to get a more efficient forecast, a complete analysis of the environment in which the aviation sector is, to understand all factors with influence over the market as a whole. Only then, the variables which would be tested for the correlation with the demand were picked. The final results of this study has achieved all objectives set and has given a better view over the European Commercial Aviation Market

Previsão do comportamento de estruturas de contenção atirantadas utilizando o software FTOOL

Population growth, together with the gradual social ascent in Brazil, reflects at the growing need for better use of urban spaces. In this context, the amount of new buildings to meet the demand in property market, the needs for creating new roads and highways, among others, make the use of geotechnical works and, more specifically, retaining walls, more and more common. One of the simplest solutions for underground works is the use of retaining structures using tie back walls for soil support, therefore, the present work deals with this kind of structures. This paper proposes the use of FTOOL software testing in predicting deformations in tie back walls, by comparing simulations of the presented model to a real and measured deformation case in Guabirotuba Formation (PR). The results showed the importance of defining the parameters such as stiffness and curtain geometry, as well as the definition of representative loads acting on it. Also, it was pointed out that the passive response of the steel rods depends on the horizontal displacement of the wall. The study concluded that the program generates very representative results when compared to field data and seems to be a promising tool for tie back structures displacement predictions

Modelos agrometeorológicos para previsão de atributos de qualidade em laranjas 'Valência' para o estado de São Paulo

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Desenvolvimento, validação, avaliação da incerteza de medição e análise de custos de método baseado em espectroscopia no infravermelho e análise multivariada para previsão de parâmetros de qualidade de amostras de E85

Pós-graduação em Química - IQ

Desenvolvimento de uma rede neuro-fuzzy para a previsão da carga

Pós-graduação em Engenharia Elétrica - FEIS

Modelos agrometeorológicos estatísticos de previsão de produtividade e qualidade para cana-de-açúcar

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Previsão de demanda para peças de reposição de alto giro: aplicação de método descritivo simples comparado com o modelo suavização exponencial

O estudo de métodos de previsão de demandas é um conceito bastante popular, mas nem sempre seus resultados são facilmente aplicáveis nas organizações por várias limitações. O propósito deste artigo é apresentar um método simples e descritivo para a previsão de demanda para peças de reposição de alto giro e comparar os resultados com o modelo de suavização exponencial. Foi utilizado para isto, dados reais de consumo de uma empresa de geração de energia em dois anos com a mesma condição de contorno, e estabeleceu-se o ano de 2012 com a série de aplicação dos métodos e a série de 2013 com a série de validação dos resultados e em todas as amostras tomadas observou-se um menor erro quadrático RMSE, a favor do método descritivo simplificado. Todas as quatro séries analisadas se caracterizam pela alta dispersão dos dados, e não possuem tendências e sazonalidades.

Modelos agrometeorológicos para previsão da produtividade e qualidade de bebida natural do cafeeiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos de previsão de ocorrência de adultos de diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) em cana-de-açúcar (Saccharum spp.)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de modelo auto-regressivo para previsão em pronto-atendimento

The 1988 constitution makes an life is a supreme good when increased health as the fundamental condition requiring that all ill patient has the right to be treated in a public hospital (CF, art. 196). In this sense, the goal of this work is to generate a weekly forecast of hospital care by means of an advanced prediction model. It is expected that the model of self-regressivas seasonal moving averages SARIMA generate reliable and adherent to issue forecasts analyzed, thus enabling better resource allocation and more efficient hospital management

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Métodos de previsão auto-regressivo aplicado a uma série de volume de produção de caminhões

The national truck fleet has expanded strongly in recent decades. However, due to fluctuations in the demand that the market is exposed, it needed up making more effective strategic decisions of automakers. These decisions are made after an evaluation of guaranteed sales forecasts. This work aims to generate an annual forecast of truck production by Box and Jenkins methodology. They used annual data for referring forecast modeling from the year 1957 to 2014, which were obtained by the National Association of Motor Vehicle Manufacturers (Anfavea). The model used was Autoregressive Integrated Moving Average (ARIMA) and can choose the best model for the series under study, and the ARIMA (2,1,3) as representative for conducting truck production forecast

Modelagem auto-regressiva na previsão de demanda dos produtos de uma empresa do setor químico

Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain