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FORECAST: técnicas de modelización, clasificación y predicción de series temporales, con aplicación al entorno marino

Authors: García, Mª Ángeles; Hernández, Isabel; Felis, Iván; Martínez, Rosa; Madrid, Eduardo;

FORECAST: técnicas de modelización, clasificación y predicción de series temporales, con aplicación al entorno marino

Abstract

Este informe, elaborado por el equipo del Centro Tecnológico Naval y del Mar, tiene como finalidad ofrecer al tejido empresarial una mejora en el conocimiento del entorno que permita detectar tendencias y desarrollar estrategias adecuadas, basadas en niveles superiores de certidumbre a través de la captación y divulgación de información y conocimiento de importancia estratégica en los ámbitos social, tecnológico y económico, que incidan en la detección de nuevas oportunidades de desarrollo regional. Los contenidos de este informe están estrechamente relacionados con el desarrollo del proyecto Investigación y optimización de técnicas de modelización, clasificación y predicción de series temporales, con aplicación al entorno marino. FORECAST aplica modelos basados en IA (Inteligencia Artificial) para encontrar una metodología óptima para el estudio de series temporales. Busca desarrollar un modelo de análisis ágil y certero que permita optimizar las tareas de predicción a través del uso de series temporales y mediante la caracterización y modelización de datos del medio marino.

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Keywords

Medio marino, Series temporales, Ámbito portuario, Acuicultura, Tecnología 4.0, Inteligencia Artificial, Modelización de datos, Modelo de análisis

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