Examinando por Materia "Aprendizaje automático"
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Ítem A retail demand forecasting system of product groups characterized by time series based on “ensemble machine learning” techniques with feature enginnering(Universidad EAFIT, 2022) Mejía Chitiva, Santiago; Aguilar Castro, José LisandroÍtem Análisis de los resultados de la aplicación del instrumento para la evaluación docente de la universidad EAFIT(Universidad EAFIT, 2024) Fernández Carmona, Laura Catalina; Guarín Zapata, Nicolás; Mola Ávila, José AntonioÍtem Análisis de registros de mantenimiento de centrales de generación de energía con técnicas de procesamiento de lenguaje natural(Universidad EAFIT, 2024) Ocampo Davila, Andrés Alonso; Salazar Martínez, Carlos AndresÍtem Aplicación de técnicas de aprendizaje automático para la proyección de la tasa de cambio entre COP y USD(Universidad EAFIT, 2022) Granada Carvajal, Lorena; Pérez Ramírez, Fredy OcarisÍtem Desarrollo de un sistema de apoyo a la toma de decisiones estilísticas en lenguaje de marca a través de una herramienta de machine learning(Universidad EAFIT, 2023) Córdoba García, Miguel de Germán; Maya Castaño, Jorge HernánÍtem Development of a machine learning-based methodology for an automatic control model in a Kaolin washing process(Universidad EAFIT, 2023) Contreras Buitrago, Oscar Javier; Martínez Vargas, Juan DavidÍtem En busca de un mayor bienestar en la ganadería de ceba y levante(2021-04-05) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Garcia, Rodriguez; Aguilas Jose; Toro Mauricio; Pinto Angel; Rodriguez Paul; Vicerrectoría de Descubrimiento y CreaciónÍtem Estimación de la distribución espacial del ingreso intra-urbano de Medellín y su área Metropolitana, usando imágenes satelitales diurnas(Universidad EAFIT, 2021) Salazar Vásquez, Jessica Patricia; Patiño Quinchía, Jorge Eduardo; Duque Cardona, Juan Carlos; Gómez Escobar, Jairo AlejandroÍtem Estrategias de trading en acciones de BVC basadas en Machine Learning. ¿Precisión implica desempeño?(Universidad EAFIT, 2022) Cerro Espinal, Carlos Alberto; Agudelo Rueda, Diego AlonsoÍtem Evaluación de una red neuronal para la solución de ecuaciones diferenciales(Universidad EAFIT, 2023) Machado-Loaiza, José Manuel; Guarín-Zapata, NicolásÍtem Hacia un modelo predictivo que apoye el logro de KPI comerciales más asertivos : caso Empresa Comercializadora de Madera(Universidad EAFIT, 2023) Tavera Rodríguez, Jhon Walter; Tabares Betancur, Marta SilviaÍtem Identificación de patrones socioeconómicos en Medellín a partir de imágenes satelitales(Universidad EAFIT, 2024) Ceballos Betancur, Mariana; Martínez Vargas, Juan David; Torres Madronero, María ConstanzaÍtem Implementación de herramientas de apoyo en el proceso de decisión del Pricing y distribución comercial para los productos del activo bancario del segmento personas dentro de la banca minorista(Universidad EAFIT, 2023) Franco Amaya, Jair Fabian; Ardila Rodríguez, Jhon Sebastian; Rojas Ormaza, Brayan RicardoÍtem Inteligencia artificial para optimizar la producción de carne(Universidad EAFIT, 2020-12-01) Martinez Guerrero, Christian Alexander; Martinez-Guerrero, Christian Alexander; García, Rodrigo; Aguilar, Jose; Toro, Mauricio; Pinto, Angel; Rodríguez, Paul; GIDITICÍtem Intelligent model for monitoring, evaluating, and recommending strategies to improve the innovation processes of MSMEs(Universidad EAFIT, 2024) Gutiérrez Buitrago, Ana Gissel; Aguilar Castro, José Lisandro; Montoya Múnera, Edwin Nelson; Ortega Álvarez, Ana MaríaThe research focuses on how to improve the innovation process in micro, small and medium-sized enterprises (MSMEs). The study is framed within the Smart Innovation paradigm. In this context, innovation is considered a relevant factor for organizational performance that allows the creation and improvement of competitive advantages through the implementation of new ideas, products, concepts, and services to increase market positioning. For organizations aiming to enhance innovation performance, using intelligent systems and artificial intelligence to guide the innovation process poses a challenge. To address this problem, the goal was to develop methodologies, models and approaches to support decision-making related to the intelligent management of the innovation process. To achieve this, specific objectives were defined. The first one is to design an intelligent model to support innovation processes in MSMEs. The second objective is to apply Artificial Intelligence (AI) techniques to customer data sources in social networks and organizational data of MSMEs, aiming to enhance the innovation process; The third objective is to develop an intelligent system to evaluate the innovation levels in MSMEs. The fourth objective is to instantiate a case study in the fashion cluster of the department of Norte de Santander and in the national context, as part of the applied methodology. To fulfill these objectives, research articles were developed. The process began with a literature review article on the current challenges in applying AI techniques to improve innovation processes in MSMEs. A proposed innovation model was made based on the different innovation models that exist in the literature, and the four research articles were written in compliance with the scientific standards that accredit them, to meet the specific objectives outlined in this doctoral thesis. Each article evaluated the strategies/models using various data sets. The results demonstrated the capacity of the proposed methodologies and models for managing of innovation processes. For instance, the proposals enable the prediction of the level of innovation, and the definition of innovation problems, among other aspects, with positive results in performance metrics.Ítem Interpreting direct sales' demand forecasts using SHAP values(Universidad EAFIT, 2022) Arboleda Flórez, Mariana; Castro Zuluaga, Carlos AlbertoÍtem Machine learning model based on LSTM networks optimized with metaheuristic algorithms to predict cardholder churn(Universidad EAFIT, 2024) Correa Jaramillo, Diana Marcela; Aguilar Castro, José LisandroÍtem Metaheuristics for vehicle routing problems with data-driven methods(Universidad EAFIT, 2024) Mesa López, Juan Pablo; Montoya Echeverri, José Alejandro; Ramos Pollán, Raúl; Toro Bermúdez, MauricioÍtem Metodología para el análisis de la similitud entre marcas mediante técnicas de aprendizaje automático(Universidad EAFIT, 2022) Echeverri Calderón, Santiago; Montoya Múnera, Edwin NelsonTrademarks consist of the symbols and words that businesses use to identify their products and services. They are often one of the most valuable assets of a company and therefore there are regulations for their registration and protection. When a trademark is registered, it gives its holder the right to prevent third parties from marketing similar products with identical or similar symbols. In trademark registration and protection processes it is necessary to determine the similarity between 2 trademarks to detect potential confusion that may mislead consumers. Traditionally, this similarity has been established through a qualitative human assessment, but given the increasing number of trademarks registration, the need to automate this task is configured. This research evaluates different techniques of Natural Language Processing (NLP), Computer Vision and phonology, applied in the context of trademark matching, to obtain a system of models that can measure visual, spelling, and phonetic similarity between trademarks. The proposed method is evaluated on a dataset of trademark registration oppositions in applications filed with the Colombian Trademark Office (Superintendencia de Industria y Comercio).Ítem Metodología para la clasificación de documentos de texto de hojas de vida basado en aprendizaje de máquina(Universidad EAFIT, 2023) Matamoros Villegas, Javier Leomar; Montoya Múnera, Edwin Nelson