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

Estudo de inibidores de corrosão em concreto armado, visando a melhoria na sua durabilidade

This thesis has as objective presents a methodology to evaluate the behavior of the corrosion inhibitors sodium nitrite, sodium dichromate and sodium molybdate, as well as your mixture, the corrosion process for the built-in steel in the reinforced concrete, through different techniques electrochemical, as well as the mechanical properties of that concrete non conventional. The addition of the inhibitors was studied in the concrete in the proportions from 0.5 to 3.5 % regarding the cement mass, isolated or in the mixture, with concrete mixture proportions of 1.0:1.5:2.5 (cement, fine aggregate and coarse aggregate), superplasticizers 2.0 % and 0.40 water/cement ratio. In the modified concrete resistance rehearsals they were accomplished to the compression, consistence and the absorption of water, while to analyze the built-in steel in the concrete the rehearsals of polarization curves they were made. They were also execute, rehearsals of corrosion potential and polarization resistance with intention of diagnose the beginning of the corrosion of the armors inserted in body-of-proof submitted to an accelerated exhibition in immersion cycle and drying to the air. It was concluded, that among the studied inhibitors sodium nitrite , in the proportion of 2.0 % in relation to the mass of the cement, presented the best capacity of protection of the steel through all the studied techniques and that the methodology and the monitoring techniques used in this work, they were shown appropriate to evaluate the behavior and the efficiency of the inhibitors