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Tesis Doctoral
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Técnicas de aprendizaje automático para la predicción de tráfico marítimo en el contexto de toma de decisiones de ámbito empresarial
(2021-10-13)
Se trata de un trabajo de investigación original sobre predicción de series temporales de tipo económico, en el que se han aplicado técnicas de aprendizaje automático. El análisis de patrones y la predicción de series ...
Ponencia
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A first prototype of a new repository for feature model exchange and knowledge sharing
(Association for Computing Machinery (ACM), 2021)
Feature models are the “de facto” standard for variability modelling and are used in both academia and industry. The MODEVAR initia tive tries to establish a common textual feature modelling language that can be used by ...
Artículo
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Generative adversarial networks for anonymized healthcare of lung cancer patients
(MDPI, 2021)
The digital twin in health care is the dynamic digital representation of the patient’s anatomy and physiology through computational models which are continuously updated from clinical data. Furthermore, used in combination ...
Artículo
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Explaining deep learning models for ozone pollution prediction via embedded feature selection
(ScienceDirect, 2024)
Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is responsible for an estimated 1 to 1.2 million premature deaths yearly. Furthermore, O3 adversely affects ...
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Artículo
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Empirical software product line engineering: A systematic literature review
(Elsevier, 2020)
Context: The adoption of Software Product Line Engineering (SPLE) is usually only based on its theoretical benefits instead of empirical evidences. In fact, there is no work that synthesizes the empirical studies on SPLE. ...
Artículo
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A Delphi study to recognize and assess systems of systems vulnerabilities
(Elsevier, 2022)
Context: System of Systems (SoS) is an emerging paradigm by which independent systems collaborate by sharing resources and processes to achieve objectives that they could not achieve on their own. In this context, a ...
Ponencia
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Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming
(Springer, 2021)
This paper presents a new forecasting algorithm for time series in streaming named StreamWNN. The methodology has two well-differentiated stages: the algorithm searches for the nearest neighbors to generate an initial ...
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