Examinando por Materia "Predicción"
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Ítem ¿Cómo libera energía la tierra?(2014) Abad Restrepo, Ana Cristina; Jaramillo Fernández, Juan Diego; Henao Toro, Mauricio; Muriel Gil, Luisa Fernanda .Ítem Competencias que mejor predicen la calidad del desempeño de las personas que trabajan en organizaciones E-commerce colombiana(Universidad EAFIT, 2022) Orduz Gómez, Natalia; Granados Gómez, Patricia Diana; Sanín Posada, John AlejandroCompetencies have the ability to predict and explain the quality of performance. In turn, performance is a predictor of the organization's productivity. This also happens in E-commerce companies. Taking into account that in Colombia this type of company generates a significant proportion of employment and it is expected that it will increase in the future. The objective of this research is to explore the competencies that best predict the quality of performance of the people who work in this type of organization. To find out about them, (eight) E-commerce experts with experience of 2 or more years in the HR area were interviewed. Through content analysis, emerging categories were built that allowed discovering the competencies that best predict the quality of performance of the people who work in these organizations in Colombia. At the end, it is discussed how these findings contribute to E-commerce organizations, organizational leaders, collaborators and human resources areas, as input for selection processes, and training.Ítem Ensemble of temporal convolutional and long short-term memory neural networks apply to forecasting USDCOP exchange rate(Universidad EAFIT, 2021) Torres Marulanda, Juan Esteban; Almonacid Hurtado, Paula MaríaThis paper applies a neural network with ensemble of temporal convolutional network (TCN) and long short-term memory (LSTM) layers approach to forecast foreign exchange rates between the US dollar (USD) and Colombian Peso (COP) and obtain a better performance. This study provides evidence on the TCN and LSTM neural network model’s effectiveness and efficiency in forecasting temporal series. It should contribute positively to developing theory, methodology, and practice of using an artificial neural network to develop a forecasting model for financial temporal series.Ítem Forecasting of time series with trend and seasonal cycle using the airline model and artificial neural networks(Universidad EAFIT, 2012-06-15) Velásquez, J D; Franco, C J; Universidad Nacional de ColombiaÍtem Forecasting stock return using a recurrent neural network apply to a financial optimization problem(Universidad EAFIT, 2021) Ochoa Ramírez, Juliana; Almonacid Hurtado, Paula MariaThis paper presents a methodological proposal for optimizing financial asset portfolios by incorporating the returns predictions instead of the historical returns to calculate an efficient frontier. We changed the return means methodology to forecast by the return with LSTM neural network. We performed several simulation exercises to evaluate the methodology with real data from the US stock market to examine our portfolio optimization model. To evaluate our results, we compared the mean-variance frontier efficiency with the neural network return model. We selected one optimal portfolio that offered the highest expected return for a defined level of risk and compare both models. We show how the neural network return model has a better performance for different periods of time, outperforming the mean-variance model at the same level.Ítem Hurto a personas en la ciudad de Medellín : análisis predictivo de la cantidad de casos en diferentes zonas de la ciudad a partir de modelos de machine learning implementando técnicas de MLOps(Universidad EAFIT, 2023) Arboleda Colorado, Jeferson Stiven; Martínez Vargas, Juan DavidRobbery of individuals in Medellín is an issue demanding immediate attention. This prompted the study of the phenomenon within an analytics project, spanning data collection, database construction, modeling, and production deployment. It's worth noting that MLOps methodology was employed utilizing AWS services. Visual tools related to the phenomenon were integrated, facilitating analysis.Ítem Incorporating a predictive component in a dynamic segmentation approach(Universidad EAFIT, 2021) Saldarriaga Aristizábal, Pablo Andrés; Laniado, Heny; Monroy, Juan CarlosÍtem Modelamiento predictivo del número de visitantes en un centro comercial(Universidad EAFIT, 2022) Rua Jaramillo, Ramón David; Laniado Rodas, Henry; Almonacid Hurtado, Paula MaríaThe ability to make predictions about the number of customers or visitors in a shopping center is a very important input in the planning and efficient use of physical and human resources in this type of company. Also, it is important to understand what aspects influences their behavior. Based on historical data on the number of visitors, as well as external (environment) variables and online search trends, a forecasting model of the behavior of daily visits to the shopping center is suggested. The historical data correspond to the pedestrian and vehicular entries (cars and motorcycles) of the last 6 years in a shopping center located in the city of Medellín. This project begins with a literature review regarding forecasting models in different places such as museums, airports, natural parks, shopping centers and restaurants, among others, in order to explore methodologies in such cases and possible solution options. Through time series analysis and machine learning algorithms, the most representative variables and the best-fit model are selected to predict the number of visitors. This model is expected to be strengthened with estimation algorithms, improving performance over time and allowing it to be applied in other business or educational environments.Ítem Modelo predictivo de la inflación en Colombia utilizando transacciones de pagos realizadas en Bancolombia(Universidad EAFIT, 2021) Acevedo Velásquez, Juan David; Arango Rúa, Jorge Iván; Puerta Álvarez, Henry Daniel; Hurtado Rendón, Álvaro ArturoÍtem Predicción de alteraciones nutricionales en función del índice peso para la talla en niños menores de 5 años, de la ciudad de Medellín(Universidad EAFIT, 2023) Bedoya Ríos, Santiago; Martínez Vargas, Juan David; Sepúlveda Cano, Lina MaríaÍtem Predicción de deserción de clientes en el mercado de seguros de transporte de carga en Estados Unidos mediante técnicas de Machine Learning : un caso de estudio(Universidad EAFIT, 2024) Uribe Durango, Víctor Ricardo; Almonacid Hurtado, Paula MaríaÍtem Predicting the entrepreneurial process phases : a machine learning approach(Universidad EAFIT, 2021) Ceballos Arias, Juan Camilo; Álvarez Barrera, Claudia Patricia; Almonacid Hurtado, Paula María