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  1. 121

    Active particles in a tube: A generalized entropy potential approach by Yongfeng Zhao

    Published 2025-01-01
    “…Our generalized entropy potential approach allows us to predict the steady-state density distribution along the tube as well as the mean-escape time out of a spindle chamber. …”
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  2. 122

    Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes by Linfeng Zhong, Yu Bai, Yan Tian, Chen Luo, Jin Huang, Weijun Pan

    Published 2021-01-01
    “…By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy (IIE) method. …”
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    On High-Dimensional Time-Variant Reliability Analysis with the Maximum Entropy Principle by Fuliang Zhou, Yu Hou, Hong Nie

    Published 2022-01-01
    “…The probability distribution of the structural response is reconstructed by the maximum entropy principle which is achieved by solving an optimization problem derived from the concept of relative entropy. …”
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  6. 126

    Statistical Entropy of Quantum Black Holes in the Presence of Quantum Gravity Effects by A. D. Kamali, H. Shababi

    Published 2018-01-01
    “…Moreover, after obtaining some thermodynamical quantities including internal energy, entropy, and heat capacity, we conclude that, at high temperature limits due to the decreasing of the number of microstates, the entropy tends to upper bounds.…”
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  7. 127

    Application of Minimum Entropy Deconvolution in the Rolling Element Bearing Fault Diagnosis by Leng Junfa, Yang Xin, Jing Shuangxi

    Published 2015-01-01
    “…Through the method of minimum entropy deconvolution( MED),the signal to noise ratio can be improved,and the impulse components from fault signal can be highlighted. …”
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  8. 128

    Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean by Henryk Gzyl, Enrique Ter Horst

    Published 2009-01-01
    “…We present a new method, based on the method of maximum entropy in the mean, which builds upon the standard method of maximum entropy, to improve the parametric estimation of a decay rate when the measurements are corrupted by large level of noise and, more importantly, when the number of measurements is small. …”
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  9. 129

    On the System Entropy and Energy Dissipativity of Stochastic Systems and Their Application in Biological Systems by Bor-Sen Chen, Xiangyun Lin, Weihai Zhang, Tianshou Zhou

    Published 2018-01-01
    “…This study discusses the relationship between the entropy and the dissipativity of stochastic systems under the background of biological systems. …”
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  10. 130
  11. 131

    A Novel Nonlinear BWR Stability Indicator Based on the Sample Entropy by Omar Alejandro Olvera-Guerrero, Alfonso Prieto-Guerrero, Gilberto Espinosa-Paredes

    Published 2018-01-01
    “…In this work a novel methodology based on the Sample entropy (SampEn) and the noise-assisted multivariate empirical mode decomposition (NA-MEMD) is introduced. …”
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  16. 136

    VDB Entropy Measures and Irregularity-Based Indices for the Rectangular Kekulene System by Weidong Zhao, K. Julietraja, P. Venugopal, Xiujun Zhang

    Published 2021-01-01
    “…Irregularity indices are numerical parameters that quantify the irregularity of a molecular graph and are used to predict some of the chemical properties, including boiling points, resistance, enthalpy of vaporization, entropy, melting points, and toxicity. This study aims to determine analytical expressions for the VDB entropy and irregularity-based indices in the rectangular Kekulene system.…”
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  17. 137

    Planetary Gearbox Fault Diagnosis based on LMD Sample Entropy and ELM by Zhang Ning, Wei Xiuye, Xu Jinhong

    Published 2020-04-01
    “…In order to solve the difficult problem of early fault feature extraction of planetary gearbox and consider that the planetary gearbox vibration signal is coupling and nonlinear,and the signal has multiple transmission paths,a planetary gearbox fault diagnosis method based on Local Mean Decomposition(LMD) and Sample Entropy and Extreme Learning Machine(ELM) is proposed.Firstly,the vibration signal is adaptively decomposed into a plurality of PF components by LMD,and the first four PF components including the main fault information are selected in combination with the correlation coefficient and the variance contribution rate.Secondly,the Sample Entropy of the signal is calculated to form a feature vector.Finally,the feature vector is input into ELM for fault classification.Experiments are carried out on the planetary gearbox test bench,compared with the probabilistic neural network classification algorithm,and compared with the feature vector based on Singular Value Decomposition (SVD).The results verify the effectiveness of the proposed method.…”
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  18. 138

    Holographic reconstruction of black hole spacetime: machine learning and entanglement entropy by Byoungjoon Ahn, Hyun-Sik Jeong, Keun-Young Kim, Kwan Yun

    Published 2025-01-01
    “…Utilizing neural ordinary differential equations alongside Monte-Carlo integration, we develop a method tailored for continuous training functions to extract the general isotropic bulk metric from entanglement entropy data. To validate our approach, we first apply our machine learning algorithm to holographic entanglement entropy data derived from the Gubser-Rocha and superconductor models, which serve as representative models of strongly coupled matters in holography. …”
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    On optimal regularity estimates for finite-entropy solutions of scalar conservation laws by Lamy, Xavier, Lorent, Andrew, Peng, Guanying

    Published 2023-03-01
    “…We consider finite-entropy solutions of scalar conservation laws $u_t +a(u)_x =0$, that is, bounded weak solutions whose entropy productions are locally finite Radon measures. …”
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