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A Methodology for the Automatic Annotation of Factuality in Spanish ; Una metodología para la anotación automática de la factualidad en español
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Clinical Concept Extraction with Lexical Semantics to Support Automatic Annotation
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In: International Journal of Environmental Research and Public Health ; Volume 18 ; Issue 20 (2021)
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Development of Machine Learning Techniques for Diabetic Retinopathy Risk Estimation
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In: TDX (Tesis Doctorals en Xarxa) (2020)
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Regrouping Attributes in Fuzzy Inference Systems ; Apprentissage par Regroupement d'Attributs dans les Systèmes d'Inférence Floue
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In: https://hal.archives-ouvertes.fr/tel-03181242 ; Apprentissage [cs.LG]. Université de Tunis El Manar, 2019. Français (2019)
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Modeling a High Concentrator Photovoltaic Module Using Fuzzy Rule-Based Systems
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In: Energies ; Volume 12 ; Issue 3 (2019)
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Abstract:
Currently, there is growing interest in the modeling of high concentrator photovoltaic modules, due to the importance of achieving an accurate model, to improve the knowledge and understanding of this technology and to promote its expansion. In recent years, some techniques of artificial intelligence, such as the Artificial Neural Network, have been used with the goal of obtaining an electrical model of these modules. However, little attention has been paid to applying Fuzzy Rule-Based Systems for this purpose. This work presents two new models of high concentrator photovoltaics that use two types of Fuzzy Systems: the Takagi-Sugeno-Kang, characterized by the achievement of high accuracy in the model, and the Mamdani, characterized by high accuracy and the ease of interpreting the linguistic rules that control the behavior of the fuzzy system. To obtain a good knowledge base, two learning methods have been proposed: the &ldquo ; Adaptive neuro-fuzzy inference system&rdquo ; and the &ldquo ; Ad Hoc data-driven generation&rdquo ; . These combinations of fuzzy systems and learning methods have allowed us to obtain two models of high concentrator photovoltaic modules, which include two improvements over previous models: an increase in the model accuracy and the possibility of deducing the relationship between the main meteorological parameters and the maximum power output of a module.
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Keyword:
ad hoc data-driven generation; adaptive neuro-fuzzy inference system; artificial neural network; fuzzy rule-based systems; high concentrator photovoltaic modules; maximum power prediction
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URL: https://doi.org/10.3390/en12030567
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Attributes regrouping in Fuzzy Rule Based Classification Systems: an intra-classes approach
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In: In the 15th ACS/IEEE International Conference on Computer Systems and Applications AICCSA 2018 ; https://hal.archives-ouvertes.fr/hal-02290131 ; In the 15th ACS/IEEE International Conference on Computer Systems and Applications AICCSA 2018, Oct 2018, Aqaba, Jordan. ⟨10.1109/AICCSA.2018.8612802⟩ (2018)
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Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?
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| 8 |
Nuevas propuestas en el ámbito de los operadores adaptativos para Sistemas Difusos Lingüísticos Evolutivos Multiobjetivo
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A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules
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Enhancing multi-class classification in FARC-HD fuzzy classifier: On the synergy between n-dimensional overlap functions and decomposition strategies
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Semantic Annotations for Workflow Interoperability
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In: ISSN: 0350-5596 ; Informatica ; https://hal.inria.fr/hal-01111453 ; Informatica, Slovene Society Informatika, Ljubljana, 2014, 38 (4), pp.347-366 (2014)
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Natural Language Semantics using Probabilistic Logic
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In: DTIC (2014)
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Updating Relational Views Using Knowledge at View Definition and View Update Time
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In: Amit P. Sheth (2014)
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Author manuscript, published in "TheoreticAl and Computational MOrphology: New Trends and Synergies (TACMO) (2013)" Continuous variation in computational morphology The example of Swiss German
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In: http://hal.archives-ouvertes.fr/docs/00/85/12/51/PDF/tacmo-abstract-ys.pdf (2013)
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| 15 |
IVTURS: a linguistic fuzzy rule-based classification system based on a new Interval-Valued fuzzy reasoning method with TUning and Rule Selection
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Aligning through divergence
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In: SNLP-AOS'2011: Joint International Symposium on Natural Language Processing and Agricultural Ontology Service ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-00839340 ; SNLP-AOS'2011: Joint International Symposium on Natural Language Processing and Agricultural Ontology Service, Feb 2012, Phuket, Thailand. pp.150-159 (2012)
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A Protocol and Tool for Developing a Descriptive Behavioral Model
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IIVFDT: Ignorance Functions based Interval-Valued Fuzzy Decision Tree with Genetic Tuning
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| 19 |
Boosting of fuzzy rules with low quality data
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In: http://sci2s.ugr.es/publications/ficheros/JMVLSC2011.pdf (2011)
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| 20 |
A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position
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