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

Modelagem e previsão da perda de injetividade em poços canhoneados

Waterflooding is a technique largely applied in the oil industry. The injected water displaces oil to the producer wells and avoid reservoir pressure decline. However, suspended particles in the injected water may cause plugging of pore throats causing formation damage (permeability reduction) and injectivity decline during waterflooding. When injectivity decline occurs it is necessary to increase the injection pressure in order to maintain water flow injection. Therefore, a reliable prediction of injectivity decline is essential in waterflooding projects. In this dissertation, a simulator based on the traditional porous medium filtration model (including deep bed filtration and external filter cake formation) was developed and applied to predict injectivity decline in perforated wells (this prediction was made from history data). Experimental modeling and injectivity decline in open-hole wells is also discussed. The injectivity of modeling showed good agreement with field data, which can be used to support plan stimulation injection wells

Um Modelo híbrido para previsão de curvas de produção de petróleo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Efeito da adição de cargas minerais leves na resistência mecânica de grautes para cimentação de poços offshore

The preparation of cement slurries for offshore well cementing involves mixing all solid components to be added to the mixing water on the platform. The aim of this work was to study the formulation of pre-prepared dry mixtures, or grouts, for offshore oilwell cementing. The addition of mineral fillers in the strength of lightweight grouts applied for depths down to 400 m under water depths of 500 m was investigated. Lightweight materials and fine aggregates were selected. For the choice of starting materials, a study of the pozzolanic activity of low-cost fillers such as porcelain tile residue, microsilica and diatomaceous earth was carried out by X-ray diffraction and mechanical strength tests. Hardened grouts containing porcelain tile residue and microsilica depicted high strength at early ages. Based on such preliminary investigation, a study of the mechanical strength of grouts with density 1.74 g/cm3 (14.5 lb/gal) cured initially at 27 °C was performed using cement, microsilica, porcelain tile residue and an anti-foaming agent. The results showed that the mixture containing 7% of porcelain tile residue and 7% of microsilica was the one with the highest compressive strength after curing for 24 hours. This composition was chosen to be studied and adapted for offshore conditions based on testes performed at 4 °C. The grout containing cement, 7% of porcelain tile residue, 7% of active silica and admixtures (CaCl2), anti-foaming and dispersant resulted satisfactory rheology and mechanical strength after curing for 24 hours of curing

Metodologia de análise e diagnóstico de fratura em um componente automotivo sujeito a cargas cíclicas alternadas

The competitiveness of the trade generated by the higher availability of products with lower quality and cost promoted a new reality of industrial production with small clearances. Track deviations at the production are not discarded, uncertainties can statistically occur. The world consumer and the Brazilian one are supported by the consumer protection code, in lawsuits against the products poor quality. An automobile is composed of various systems and thousands of constituent parts, increasing the likelihood of failure. The dynamic and security systems are critical in relation to the consequences of possible failures. The investigation of the failure gives us the possibility of learning and contributing to various improvements. Our main purpose in this work is to develop a systematic, specific methodology by investigating the root cause of the flaw occurred on an axle end of the front suspension of an automobile, and to perform comparative data analyses between the fractured part and the project information. Our research was based on a flaw generated in an automotive suspension system involved in a mechanical judicial cause, resulting in property and personal damages. In the investigations concerning the analysis of mechanical flaws, knowledge on materials engineering plays a crucial role in the process, since it enables applying techniques for characterizing materials, relating the technical attributes required from a respective part with its structure of manufacturing material, thus providing a greater scientific contribution to the work. The specific methodology developed follows its own flowchart. In the early phase, the data in the records and information on the involved ones were collected. The following laboratory analyses were performed: macrography of the fracture, micrography with SEM (Scanning Electron Microscope) of the initial and final fracture, phase analysis with optical microscopy, Brinell hardness and Vickers microhardness analyses, quantitative and qualitative chemical analysis, by using X-ray fluorescence and optical spectroscopy for carbon analysis, qualitative study on the state of tension was done. Field data were also collected. In the analyses data of the values resulting from the fractured stock parts and the design values were compared. After the investigation, one concluded that: the developed methodology systematized the investigation and enabled crossing data, thus minimizing diagnostic error probability, the morphology of the fracture indicates failure by the fatigue mechanism in a geometrically propitious location, a tension hub, the part was subjected to low tensions by the sectional area of the final fracture, the manufacturing material of the fractured part has low ductility, the component fractured in an earlier moment than the one recommended by the manufacturer, the percentages of C, Si, Mn and Cr of the fractured part present values which differ from the design ones, the hardness value of the superior limit of the fractured part is higher than that of the design, and there is no manufacturing uniformity between stock and fractured part. The work will contribute to optimizing the guidance of the actions in a mechanical engineering judicial expertise

Viabilidade de utilização de um compósito de matriz cerâmica com cargas recicláveis na fabricação de equipamentos solares

Composite materials can be defined as materials formed from two or more constituents with different compositions, structures and properties, which are separated by an interface. The main objective in producing composites is to combine different materials to produce a single device with superior properties to the component unit. The present study used a composite consisting of plaster, cement, EPS, tire, PET and water to build prototype solar attempt to reduce the manufacturing cost of such equipment. It was built two box type solar cookers, a cooler to be cooled by solar energy, a solar dryer and a solar cooker concentration. For these prototypes were discussed the processes of construction and assembly, determination of thermal and mechanical properties, and raising the performance of such solar systems. Were also determined the proportions of the constituents of the composite materials according to specific performance of each prototype designed. This compound proved to be feasible for the manufacture of such equipment, low cost and easy manufacturing and assembly processes

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Avaliação mecânica e microestrutural de compósitos de poliéster com adição de cargas minerais e resíduos industriais

With the current growth in consumption of industrialized products and the resulting increase in garbage production, their adequate disposal has become one of the greatest challenges of modern society. The use of industrial solid residues as fillers in composite materials is an idea that emerges aiming at investigating alternatives for reusing these residues, and, at the same time, developing materials with superior properties. In this work, the influence of the addition of sand, diatomite, and industrial residues of polyester and EVA (ethylene vinyl acetate), on the mechanical properties of polymer matrix composites, was studied. The main objective was to evaluate the mechanical properties of the materials with the addition of recycled residue fillers, and compare to those of the pure polyester resin. Composite specimens were fabricated and tested for the evaluation of the flexural properties and Charpy impact resistance. After the mechanical tests, the fracture surface of the specimens was analyzed by scanning electron microscopy (SEM). The results indicate that some of the composites with fillers presented greater Young s modulus than the pure resin; in particular composites made with sand and diatomite, where the increase in modulus was about 168 %. The composites with polyester and EVA presented Young s modulus lower than the resin. Both strength and maximum strain were reduced when fillers were added. The impact resistance was reduced in all composites with fillers when compared to the pure resin, with the exception of the composites with EVA, where an increase of about 6 % was observed. Based on the mechanical tests, microscopy analyses and the compatibility of fillers with the polyester resin, the use of industrial solid residues in composites may be viable, considering that for each type of filler there will be a specific application

Estudo da previsão da carga de ruptura de estacas pré-moldadas de concreto

The piles are one of the most important types of solution adopted for the foundation of buildings. They are responsible for transmitting to the soil in deepe r and resistant layers loads from structures. The interaction of the foundation element with the soil is a very important variable, making indispensable your domain in order to determine the strength of the assembly and establish design criteria for each c ase of application of the pile. In this research analyzes were performed f rom experiments load tests for precast concrete piles and inve stigations of soil of type SPT, a study was performed for obtaining the ultimate load capacity of the foundation through methods extrapolation of load - settlement curve , semi - empirical and theoretic . After that, were realized comparisons between the different methods used for two types of soil a granular behavior and other cohesive. For obtaining soil paramet ers to be used i n the methods were established empirical correlations with the standard penetration number (NSPT). The charge - settlement curves of the piles are also analyzed. In the face of established comparisons was indicated the most reliable semiempirical method Déco urt - Quaresma as the most reliable for estimating the tensile strength for granular and cohesive soils. Meanwhile, among the methods studied extrapolation is recommended method of Van der Veen as the most appropriate for predicting the tensile strength.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Ordenamento de cargas e propriedades magnéticas de ortoferritas de lantânio dopadas com estrôncio

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ordenamento de cargas e propriedades magnéticas de ortoferritas de lantânio dopadas com estrôncio

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito do treinamento muscular inspiratório com diferentes cargas na força e função de músculos respiratórios

Background: The inspiratory muscle training (IMT) has been considered an option in reversing or preventing decrease in respiratory muscle strength, however, little is known about the adaptations of these muscles arising from the training with charge. Objectives: To investigate the effect of IMT on the diaphragmatic muscle strength and function neural and structural adjustment of diaphragm in sedentary young people, compare the effects of low intensity IMT with moderate intensity IMT on the thickness, mobility and electrical activity of diaphragm and in inspiratory muscles strength and establish a protocol for conducting a systematic review to evaluate the effects of respiratory muscle training in children and adults with neuromuscular diseases. Materials and Methods: A randomized, double-blind, parallel-group, controlled trial, sample of 28 healthy, both sexes, and sedentary young people, divided into two groups: 14 in the low load training group (G10%) and 14 in the moderate load training group (G55%). The volunteers performed for 9 weeks a home IMT protocol with POWERbreathe®. The G55% trained with 55% of maximal inspiratory pressure (MIP) and the G10% used a charge of 10% of MIP. The training was conducted in sessions of 30 repetitions, twice a day, six days per week. Every two weeks was evaluated MIP and adjusted the load. Volunteers were submitted by ultrasound, surface electromyography, spirometry and manometer before and after IMT. Data were analyzed by SPSS 20.0. Were performed Student's t-test for paired samples to compare diaphragmatic thickness, MIP and MEP before and after IMT protocol and Wilcoxon to compare the RMS (root mean square) and median frequency (MedF) values also before and after training protocol. They were then performed the Student t test for independent samples to compare mobility and diaphragm thickness, MIP and MEP between two groups and the Mann-Whitney test to compare the RMS and MedF values also between the two groups. Parallel to experimental study, we developed a protocol with support from the Cochrane Collaboration on IMT in people with neuromuscular diseases. Results: There was, in both groups, increased inspiratory muscle strength (P <0.05) and expiratory in G10% (P = 0.009) increase in RMS and thickness of relaxed muscle in G55% (P = 0.005; P = 0.026) and there was no change in the MedF (P> 0.05). The comparison between two groups showed a difference in RMS (P = 0.04) and no difference in diaphragm thickness and diaphragm mobility and respiratory muscle strength. Conclusions: It was identified increased neural activity and diagrammatic structure with consequent increase in respiratory muscle strength after the IMT with moderate load. IMT with load of 10% of MIP cannot be considered as a placebo dose, it increases the inspiratory muscle strength and IMT with moderate intensity is able to enhance the recruitment of muscle fibers of diaphragm and promote their hypertrophy. The protocol for carrying out the systematic review published in The Cochrane Library.

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