Listar Lenguajes y Ciencias de la Computación - (LCC) por tipo "info:eu-repo/semantics/acceptedVersion"
Mostrando ítems 1-6 de 6
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A data mining system for predicting solar global spectral irradiance. Performance assessment in the spectral response ranges of thin-film photovoltaic modules
Del-Campo-Ávila, José
; Piliougine, Michel; Morales-Bueno, Rafael; Mora-López, Llanos (Elsevier Ltd., 2019-04)
Knowing the spectral distribution of solar radiation is required to estimate the performance of photovoltaic modules, especially for thin-film modules. This is not a trivial problem due to the large number of environmental ... -
Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation
Del-Campo-Ávila, José; Takilalte, Abdelatif; Bifet, Albert; Mora-López, Llanos (Elsevier Ltd, 2021-04-01)
A new methodology to predict one-day-ahead hourly solar global radiation is proposed in this paper. This information is very useful to address many real problems; for instance, energy-market decision making is one of the ... -
Fault localization in DSLTrans model transformations by combining symbolic execution and spectrum-based analysis
Oakes, Bentley James; Troya-Castilla, Javier; Galasso, Jessie; Wimmer, Manuel (Springer Nature, 2023-09-29)
The verification of model transformations is important for realizing robust model-driven engineering technologies and quality-assured automation. Many approaches for checking properties of model transformations have been ... -
Improved detection of small objects in road network sequences using CNN and super resolution
The detection of small objects is one of the problems present in deep learning due to the context of the scene or the low number of pixels of the objects to be detected. According to these problems, current pre-trained ... -
NORA: Scalable OWL reasoner based on NoSQL databasesand Apache Spark
Benítez-Hidalgo, Antonio; Navas-Delgado, Ismael; Roldán-García, María del Mar (Wiley, 2023-09-04)
Reasoning is the process of inferring new knowledge and identifying inconsis-tencies within ontologies. Traditional techniques often prove inadequate whenreasoning over large Knowledge Bases containing millions or billions ... -
Online and Non-Parametric Drift Detection Methods Based on Hoeffding’s Bounds
Frías-Blanco, Isvani; Del-Campo-Ávila, José; Ramos-Jiménez, Gonzalo Pascual; Morales-Bueno, Rafael; Ortiz-Díaz, Agustín; Caballero-Mota, Yailé[et al.] (IEEE, 2015-03-01)
Incremental and online learning algorithms are more relevant in the data mining context because of the increasing necessity to process data streams. In this context, the target function may change over time, an inherent ...