Browsing by Subject "Séries temporais"
Now showing items 1-15 of 15
-
Análise de séries temporais multivariadas via Wavelet
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 24/08/2023)After the mid-1980s, wavelet theory quickly spread to many fields. Although wavelet analysis has the ability to decompose data into various time scales and to deal with nonstationary data and time location, this methodology ... -
Time series forecasting : advances on Theta method
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Estatística - PPGEs, Câmpus São Carlos, 13/05/2016)Accurate and robust forecasting methods for univariate time series are critical as the historical data can be used in the strategic planning of such future operations as buying and selling to ensure product inventory and ... -
Análise comparativa entre técnicas de aprendizado de máquina aplicadas para a predição de preços de produtos hortifrutícolas
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 29/08/2023)Family farming is characterized as any form of land cultivation managed by a family, employing its own members as the main labor force. Most agricultural establishments in Brazil fit this definition, however, the area ... -
Método bagging para aprimoramento de previsões de séries temporais
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/10/2021)Different methodologies are proposed and explored aiming to reduce time series forecasting error. A promising approach consists in combining different forecasts from different models in order to get a better accuracy, ... -
Predição de carga de energia elétrica no Brasil utilizando técnicas de Deep Learning
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 22/10/2022)The open electricity market has stood out for being a competitive and dynamic way of trading an asset that was previously restricted to passive consumption. The freedom of negotiation provided to the participants of this ... -
Estudo e comparação das técnicas de validação cruzada desenvolvidas para séries temporais
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 18/04/2022)Testing the generalization capacity of an algorithm obtained is crucial for any prediction methodology, for which cross-validation methods were developed. However, when dealing with data that have dependency among observations, ... -
Modelagem da volatilidade em séries temporais financeiras via modelos GARCH com abordagem bayesiana
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 18/07/2017)In the last decades volatility has become a very important concept in the financial area, being used to measure the risk of financial instruments. In this work, the focus of study is the modeling of volatility, that ... -
Enhancing solar flare forecasting: a multi-class and multi-label classification approach to handle imbalanced time series
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 21/06/2019)Solar flares are huge releases of energy from the Sun. They are categorized in five levels according to their potential damage to Earth (A, B, C, M, and X) and may produce strong impacts to communication systems, threatening ... -
Análise do material particulado na área central da cidade de São Carlos-SP através de técnicas espectroanalíticas e avaliação multidimensional de séries temporais
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Engenharia Química - PPGEQ, Câmpus São Carlos, 23/05/2019)Due to the worldwide trend of industrialization and urbanization, air pollutants are emitted large quantities on a global scale, particularly in developing countries, which produces adverse effects on human health by ... -
Biotic factors drive bacterioplankton community in a tropical coastal site of the equatorial atlantic ocean
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ecologia e Recursos Naturais - PPGERN, Câmpus São Carlos, 01/09/2016)The relationship between latitude and microbial diversity in the ocean is controversial. Niche models predict higher richness at high latitudes in winter, while snapshot field-sampling point towards higher richness at ... -
Modelo de Séries Temporais Autorregressivo Periódico - PAR
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 20/06/2021)This work presents the study of a type of time series model, called of periodic autoregressive model, which emerged from the researches of Thomas and Fiering (1962), according to Hipel and McLeod (1994). Its use is mainly ... -
Um estudo sobre wavestrap
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 30/06/2021)Wavelets are basis of function spaces that can be used to represent both continuous (functions) and discrete (sequences) signals; wavelets study gained great notoriety after the work of Daubechies, who developed a wavelet ... -
Efeitos da Lei Maria da Penha na Região Sudeste
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 11/12/2020)In Brazil, records of domestic violence and femicide are considered very high and represent one of the most expressive forms of violence in the country. It is of interest to investigate the behavior of these registered ... -
Estudo do teste SNHT (Standart Normal Homogeneity Test) para detecção de pontos de mudança em séries temporais
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 20/06/2021)The study of time series is extremely important for a better understanding how certain events develop over time. To do this, be able to to indicate the exact moment when a given phenomenon changes its pattern of behavior ... -
Análise sobre o fator temporal em tarefas de quantificação com dados textuais
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 13/12/2023)The quantification task, a recently discovered field in machine learning, estimates the class distribution of a dataset. Usually, quantification tasks are solved through classifica- tion, an inducted classifier predicts ...