Análises, aplicações e validações–numérico/experimentais do modelo SWAN em áreas restritas e ao largo

Pós-graduação em Engenharia Elétrica - FEIS

The bias in reversing the Box-Cox transformation in time series forecasting: An empirical study based on neural networks

The Box-Cox transformation is a technique mostly utilized to turn the probabilistic distribution of a time series data into approximately normal. And this helps statistical and neural models to perform more accurate forecastings. However, it introduces a bias when the reversion of the transformation is conducted with the predicted data. The statistical methods to perform a bias-free reversion require, necessarily, the assumption of Gaussianity of the transformed data distribution, which is a rare event in real-world time series. So, the aim of this study was to provide an effective method of removing the bias when the reversion of the Box-Cox transformation is executed. Thus, the developed method is based on a focused time lagged feedforward neural network, which does not require any assumption about the transformed data distribution. Therefore, to evaluate the performance of the proposed method, numerical simulations were conducted and the Mean Absolute Percentage Error, the Theil Inequality Index and the Signal-to-Noise ratio of 20-step-ahead forecasts of 40 time series were compared, and the results obtained indicate that the proposed reversion method is valid and justifies new studies. (C) 2014 Elsevier B.V. All rights reserved.

Tendências hidrológicas anuais e sazonais na bacia do Rio Paraibuna, Parque Estadual da Serra do Mar (SP)

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

AVALIAÇÃO ROBUSTA DA MODELAGEM NEUTROSFÉRICA SOBRE O TERRITÓRIO BRASILEIRO BASEADA EM MODELOS DE PREVISÃO NUMÉRICA DE TEMPO DA AMÉRICA DO SUL

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

Trends in Mean Annual Streamflows in Serra da Mantiqueira Environmental Protection Area

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

Water use of Juniperus virginiana trees encroached into mesic prairies in Oklahoma, USA

Juniperus virginiana (eastern redcedar) is encroaching into mesic prairies of the southern Great Plains, USA, and is altering the hydrologic cycle. We used the thermal dissipation technique to quantify daily water use of J. virginiana into a mesic prairie by measuring 19 trees of different sizes from different density stands located in north-central Oklahoma during 2011. We took the additional step to calibrate our measurements by comparing thermal dissipation technique estimates to volumetric water use for a subset of trees. Except for days with maximum air temperature below -3 degrees C, J. virginiana trees used water year round, reached a peak in late May, and exhibited reduced water use in summer when soil water availability was low. Overall daily average water use was 24 l (+/- 21.81 s.d.) per tree. Trees in low density stands used more water than trees with similar diameters from denser stands. However, there was no difference in water use between trees in different density stands when expressed on a canopy area basis. Approximately 50% of variation in water use that remained after accounting for the factors site, tree, and day was explained using a physiologically-based model that included daily potential evapotranspiration, maximum vapour pressure deficit, maximum temperature, solar radiation, and soil water storage between 0 and 10 cm. Our model suggested that a J. virginiana woodland with a closed canopy is capable of transpiring almost all precipitation reaching the soil in years with normal precipitation, indicating the potential for encroachment to reduce water yield for streamflow and groundwater recharge. Copyright (C) 2013 John Wiley & Sons, Ltd.

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

Contribuição das águas subterrâneas para a vazão do Ribeirão Boa Vista ou Córrego do Lajeado

This paper aimed to give a contribution to improve water resources management, consists of the analysis of interaction among groundwater and streamflow, by through the analysis of the relationship between basic and total streamflow, based on measured hidrological data from Ribeirão Boa Vista or Córrego Lajeado. watershed. Comparisons among groundwaterflow in this basin with another one in Rio Corumbataí basin were made based on the specific basic flow, in order to verify the possibility of the utilization of measured hydrological data in other basins with similar geological characteristics and soil use and occupation. Based upon the comparisons that were made, specific basic flow does not represent a good tool for extrapolation of measured data, indicating that this comparison shall be weighted by others characteristics as permeability and thickness of geological formations. Finally, it was possible to conclude that basic flow may be considered as an additional parameter for analysis of hydrological and hydrogeological characteristics of a basin and to provide subsidies to release legal licenses for water resources uses. related to surface water as well as for groundwater and may also be used as a tool for consolidation of integrated management of water resources, that is considered as a necessary and essential practice to avoid conflicts between users of water resources in a river basin.

Métodos econométricos para a análise do índice de inflação no Brasil

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

Aplicação de modelos hidrológicos para avaliação de reservatórios de retenção e detenção combinados à obra de recuperação do canal de macrodrenagem no controle de cheias em uma bacia hidrográfica urbanizada

The aim of this paper was to evaluate the effect of retention and detention reservoirs along with the regulation in channel flow upgrade on flood for an urban watershed located at Rio Claro, SP. For this purpose, modeling and simulation techniques were applied for runoff determination and its propagation in channel. The Soil Conservation Service – SCS hydrologic model as well as Pulz and non-linear Muskingum-Cunge model were used. The software IPHS1 was applied on simulations. The results pointed out that the combination of retention increasing and detention reservoir implementation (120,000 m3, corresponding to 1.5% of the watershed area) with the streamflow upgrade (n decreasing from 0,04 to 0,02) can minimize the flood on the investigated Servidão watershed. Further, after the proposed intervention, the flood was eliminated for the investigated times of recurrence: 5, 20, 50 and 100 years. The prognostic indicated that the available area occupation had a minor effect on flow increasing due to the observed high urbanization.

Combinando sistemas de informação geográfica e redes neurais GMDH para prever densidades demográficas

The aim of this work is to advance a new approach for estimating demographic density, through combining a Geographic Information System with GMDH Neural Networks. The model that is suggested parts the analyzed space into a rectangular grid formed by multiple cells measuring 0.01 km2 each. The forecasts are elaborated based on the demographic density in each cell and in its neighboring cells at a given time. Despite the limited availability of data during the modeling phase, the utilization of this method for studying a Brazilian medium-sized city presented promising results.

Envelhecimento e sociedade: um debate sobre o lugar do idoso no Brasil contemporâneo

Pós-graduação em Ciências Sociais - FFC

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

Implementação do OEE nas máquinas de laminação a frio

Through a description of the productivity problems experienced by some enterprises, to optimize their respective production lines, results of poor performance or low quality, the following work aims to explain and demonstrate the practical application of the theory of overall equipment effectiveness (OEE) on cold lamination machines in a steel industry . The project, to ensure your goal, is based on structuring a complete planning to increase levels of performance, availability and quality relating to rolling. On completion of the work, will be presented forecasts of future goals for the OEE, to search for continuous improvement and global standards of efficiency, taking into account, the sector the company operates, the history of the laminators, and financial aspects

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