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Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas [PDF]
EntropyLearning dependence graphs from multivariate continuous data is challenging when marginal distributions are heterogeneous, since likelihood-based nonparametric scores can be sensitive to smoothing choices and can confound marginal irregularities ...
Luiz Desuó Neto +3 more
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The sustainability of recreational sports in Chinese cities based on cognitive entropy. [PDF]
PLoS ONEWith progress of science and development of economy, increasing numbers of urban residents take part in recreational sports (RS) due to their more leisure time and increased income.
Xuefang Zou +4 more
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Analysis of entropies based on empirical mode decomposition in amnesic mild cognitive impairment of diabetes mellitus [PDF]
Journal of Innovative Optical Health Sciences, 2015 EEG characteristics that correlate with the cognitive functions are important in detecting mild cognitive impairment (MCI) in T2DM. To investigate the complexity between aMCI group and age-matched non-aMCI control group in T2DM, six entropies combining ...
Dong Cui +5 more
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Wavelet-Based Entropy Measures to Characterize Two-Dimensional Fractional Brownian Fields [PDF]
, 2020 The aim of this work was to extend the results of Perez et al. (Physica A (2006), 365 (2), 282–288) to the two-dimensional (2D) fractional Brownian field. In particular, we defined Shannon entropy using the wavelet spectrum from which the Hurst exponent is
Contreras-Reyes, Javier +2 more
core +1 more source
IEEE Access, 2021 For multidimensional data, Space-Filling Curves (SFCs) have been used to improve the execution time of spatial data queries. However, their effect on compression, when used to reorder the uncompressed values, is known to a lesser extent.
Conrad J. Haupt +2 more
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A Robust Machine Learning Model for Diabetic Retinopathy Classification
Journal of Imaging, 2023 Ensemble learning is a process that belongs to the artificial intelligence (AI) field. It helps to choose a robust machine learning (ML) model, usually used for data classification.
Gigi Tăbăcaru +3 more
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A Fuzzy Entropy-Based Group Consensus Measure for Financial Investments
Mathematics, 2023 This study presents a novel, fuzzy entropy-based approach to the measurement of consensus in group decision making. Here, the basic assumption is that the decision inputs are the ‘yes’ or ‘no’ votes of group members on a financial investment that has a ...
József Dombi +2 more
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Long Memory and Volatility Clustering: is the empirical evidence consistent across stock markets? [PDF]
, 1994 Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia.
Bentes, Sonia R. +2 more
core +5 more sources
Entropy, 2016 Additional entropy generation rates through non-equilibrium ordered structures are predicted for corner flows with sidewall mass injection. Well-defined non-equilibrium ordered structures are predicted at a normalized vertical station of approximately ...
LaVar King Isaacson
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Random Noise Suppression Method of Micro-Seismic Data Based on CEEMDAN-FE-TFPF
Applied Sciences, 2022 As rock fractures caused by micro-seismic events has potential safety hazards to underground workers, it is often necessary to accurately locate the micro-seismic source for hidden danger investigation.
Jianting Chen +5 more
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