Examinando por Autor "Astudillo, Gabriel"

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  • Miniatura
    Ítem
    Copper Price Prediction Using Support Vector Regression Technique
    (MDPI, 2020) Astudillo, Gabriel; Carrasco, Raúl; Fernández-Campusano, Christian; Chacón, Máx
    Predicting copper price is essential for making decisions that can affect companies and governments dependent on the copper mining industry. Copper prices follow a time series that is nonlinear and non-stationary, and that has periods that change as a result of potential growth, cyclical fluctuation and errors. Sometimes, the trend and cyclical components together are referred to as a trend-cycle. In order to make predictions, it is necessary to consider the different characteristics of a trend-cycle. In this paper, we study a copper price prediction method using support vector regression (SVR). This work explores the potential of the SVR with external recurrences to make predictions at 5, 10, 15, 20 and 30 days into the future in the copper closing price at the London Metal Exchange. The best model for each forecast interval is performed using a grid search and balanced cross-validation. In experiments on real data sets, our results obtained indicate that the parameters (C, ε, γ) of the model support vector regression do not differ between the different prediction intervals. Additionally, the amount of preceding values used to make the estimates does not vary according to the predicted interval. Results show that the support vector regression model has a lower prediction error and is more robust. Our results show that the presented model is able to predict copper price volatilities near reality, as the root-mean-square error (RMSE) was equal to or less than the 2.2% for prediction periods of 5 and 10 days.
  • Miniatura
    Ítem
    Evaluation of the Implementation of Li-Fi in the Communes of Santiago
    (Springer Nature, 2020) González, Alvaro; Castillo, Juan C.; Carrasco, Raúl; Lagos, Carolina; Viera, Eduardo; Banguera, Leonardo; Astudillo, Gabriel
    This work seeks to implement the functioning of a network communication system, this is done through visible light in the urban sectors of the metropolitan region. While it should be known that, Li-Fi (Light Fidelity) is a wireless communication system that uses visible light as a means of data propagation, becoming an alternative to wireless radio frequency systems. The multicriteria method called Elimination et Choix Traduisant la R´ealit´e (ELECTRE). An extended version of ELECTRE I method will be used to obtain a reliable result, since it is possible to obtain a decision with several alternatives, deriving a single solution from the analysis. It must be taken into account that the election process is about the correct place to implement Li-Fi connections, taking into account as a dependent variable places with a better standard of living in the Metropolitan Region, and random variables will be about areas of interest such as; physical, climatological, among others. Likewise, it must be borne in mind that the advantages, disadvantages and hierarchy are evaluated in order of preference.
  • Miniatura
    Ítem
    Experimental Framework to Simulate Rescue Operations after a Natural Disaster
    (Universidad Nacional de La Plata: Facultad de Informática, 2020) Veas-Castillo, Luis; Ovando-Leon, Gabriel; Astudillo, Gabriel; Gil-Costa, Veronica; Marín, Mauricio
    Computational simulation is a powerful tool for performance evaluation of computational systems. It is useful to make capacity planning of data center clusters, to obtain profiling reports of software applications and to detect bottlenecks. It has been used in different research areas like large scale Web search engines, natural disaster evacuations, computational biology, human behavior and tendency, among many others. However, properly tuning the parameters of the simulators, defining the scenarios to be simulated and collecting the data traces is not an easy task. It is an incremental process which requires constantly comparing the estimated metrics and the flow of simulated actions against real data. In this work, we present an experimental framework designed for the development of large scale simulations of two applications used upon the occurrence of a natural disaster strikes. The first one is a social application aimed to register volunteers and manage emergency campaigns and tasks. The second one is a benchmark application a data repository named MongoDB. The applications are deployed in a distributed platform which combines different technologies like a Proxy, a Containers Orchestrator, Containers and a NoSQL Database. We simulate both applications and the architecture platform. We validate our simulators using real traces collected during simulacrums of emergency situations.