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Journal articles on the topic 'Entropy methods'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Chinenye Ezeh, Chinenye Ezeh, Tao Ren Chinenye Ezeh, Yan-Jie Xu Tao Ren, Shi-Xiang Sun Yan-Jie Xu, and Zhe Li Shi-Xiang Sun. "Entropy and Structural-Hole Based Node Ranking Methods." 網際網路技術學刊 22, no. 5 (2021): 1009–17. http://dx.doi.org/10.53106/160792642021092205007.

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2

Lozano, Carlos. "Entropy and Adjoint Methods." Journal of Scientific Computing 81, no. 3 (2019): 2447–83. http://dx.doi.org/10.1007/s10915-019-01092-0.

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3

Temursho, Umed. "Entropy-based benchmarking methods." Statistica Neerlandica 72, no. 4 (2018): 421–46. http://dx.doi.org/10.1111/stan.12160.

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4

Osara, Jude A., and Michael D. Bryant. "Methods to Calculate Entropy Generation." Entropy 26, no. 3 (2024): 237. http://dx.doi.org/10.3390/e26030237.

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Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real-time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, interna

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5

Flood, Matthew W., and Bernd Grimm. "EntropyHub: An open-source toolkit for entropic time series analysis." PLOS ONE 16, no. 11 (2021): e0259448. http://dx.doi.org/10.1371/journal.pone.0259448.

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An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods. To da

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6

SHAMILOV, Aladdin, and Nihal İNCE. "On Several New Generalized Entropy Optimization Methods." Turkiye Klinikleri Journal of Biostatistics 8, no. 2 (2016): 110–15. http://dx.doi.org/10.5336/biostatic.2016-52369.

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7

Dobrzynski, L. "Bayesian and Maximum Entropy Methods." Physica Scripta 79, no. 4 (2008): 040201. http://dx.doi.org/10.1088/0031-8949/79/4/040201.

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8

TAIMRE, THOMAS. "ADVANCES IN CROSS-ENTROPY METHODS." Bulletin of the Australian Mathematical Society 80, no. 3 (2009): 521–22. http://dx.doi.org/10.1017/s0004972709000781.

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9

Brereton, R. G. "Entropy methods in chemical dataprocessing." Chemometrics and Intelligent Laboratory Systems 12, no. 3 (1991): 305–7. http://dx.doi.org/10.1016/0169-7439(92)80016-w.

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10

Alizadeh Noughabi, Hadi. "Entropy Estimation Using Numerical Methods." Annals of Data Science 2, no. 2 (2015): 231–41. http://dx.doi.org/10.1007/s40745-015-0045-9.

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11

Chan, Jesse. "On discretely entropy conservative and entropy stable discontinuous Galerkin methods." Journal of Computational Physics 362 (June 2018): 346–74. http://dx.doi.org/10.1016/j.jcp.2018.02.033.

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12

Li, Min, Yunjie Fang, Yu Zhang, et al. "Epileptic EEG information entropy based on different entropy estimation methods." Journal of Physics: Conference Series 1592 (August 2020): 012039. http://dx.doi.org/10.1088/1742-6596/1592/1/012039.

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13

Jamin, Antoine, and Anne Humeau-Heurtier. "(Multiscale) Cross-Entropy Methods: A Review." Entropy 22, no. 1 (2019): 45. http://dx.doi.org/10.3390/e22010045.

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Cross-entropy was introduced in 1996 to quantify the degree of asynchronism between two time series. In 2009, a multiscale cross-entropy measure was proposed to analyze the dynamical characteristics of the coupling behavior between two sequences on multiple scales. Since their introductions, many improvements and other methods have been developed. In this review we offer a state-of-the-art on cross-entropy measures and their multiscale approaches.

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14

Huang, Yanyan, Hongli Zhao, Yunzhong Jiang, Xin Lu, Zheng Hao, and Hao Duan. "Comparison and Analysis of Different Discrete Methods and Entropy-Based Methods in Rain Gauge Network Design." Water 11, no. 7 (2019): 1357. http://dx.doi.org/10.3390/w11071357.

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A reasonable rain gauge network layout can provide accurate regional rainfall data and effectively support the monitoring, development and utilization of water resources. Currently, an increasing number of network design methods based on entropy targets are being applied to network design. The discretization of data is a common method of obtaining the probability in calculations of information entropy. To study the application of different discretization methods and different entropy-based methods in the design of rain gauge networks, this paper compares and analyzes 9 design results for rainy

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15

Girardin, Valerie, and Nikolaos Limnios. "Entropy Rate and Maximum Entropy Methods for Countable Semi-Markov Chains." Communications in Statistics - Theory and Methods 33, no. 3 (2004): 609–22. http://dx.doi.org/10.1081/sta-120028687.

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16

Borysenko, Oleksiy. "BINOMIAL METHODS FOR BINARY MESSAGE COMPRESSION." Grail of Science, no. 21 (November 5, 2022): 96–101. http://dx.doi.org/10.36074/grail-of-science.28.10.2022.017.

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Two lossless numerical compression methods for binary messages using binomial coefficients are proposed. The methods are based on the decomposition of a Bernoulli source of information into a combinatorial source A and a probabilistic source B. Accordingly, the entropy of the source is also decomposed into two entropies. The entropy of source A solves the problem of enumeration encoding of compressible messages, and the entropy of source B for the first method solves the problem of optimal coding. The disadvantage of this method is the need for statistical tests. In the second method, the calc

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17

Guel-Cortez, Adrian-Josue, and Eun-Jin Kim. "Relations between entropy rate, entropy production and information geometry in linear stochastic systems." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 3 (2023): 033204. http://dx.doi.org/10.1088/1742-5468/acbc24.

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Abstract In this work, we investigate the relation between the concept of ‘information rate’, an information geometric method for measuring the speed of the time evolution of the statistical states of a stochastic process, and stochastic thermodynamics quantities like entropy rate and entropy production. Then, we propose the application of entropy rate and entropy production to different practical applications such as abrupt event detection, correlation analysis, and control engineering. Specifically, by utilising the Fokker–Planck equation of multi-variable linear stochastic processes describ

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18

Mohamed, Noufal Zerhouni, and Özarı Çiğdem. "Assessment of International Digital Economy and Society Index Using Entropy based TOPSIS Methods." International Journal of Recent Research in Commerce Economics and Management 9, no. 2 (2022): 70–77. https://doi.org/10.5281/zenodo.6579884.

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<strong>Abstract:</strong> This paper assesses the International Digital Economy and Society Index (I-DESI) which measures the development of the digital economy. Based on the European Commission’s I-DESI database of 45 countries from 2015 to 2018, the study compares criteria weights initially used for dimensions against new ones calculated using the Entropy method. Then, it recalculates the I-DESI using three different methods (Entropy, TOPSIS and Entropy-based TOPSIS) and finally compares countries rankings using Spearman’s correlation and Kendall W test. Results show that calcul

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19

Abbas, A. E. "Entropy Methods for Adaptive Utility Elicitation." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 34, no. 2 (2004): 169–78. http://dx.doi.org/10.1109/tsmca.2003.822269.

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20

Hoayek, Anis, and Didier Rullière. "Assessing clustering methods using Shannon's entropy." Information Sciences 689 (January 2025): 121510. http://dx.doi.org/10.1016/j.ins.2024.121510.

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21

Milman, Vitali, and Alain Pajor. "Entropy methods in asymptotic convex geometry." Comptes Rendus de l'Académie des Sciences - Series I - Mathematics 329, no. 4 (1999): 303–8. http://dx.doi.org/10.1016/s0764-4442(00)88571-7.

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22

Greco, F., and M. Arroyo. "High-order maximum-entropy collocation methods." Computer Methods in Applied Mechanics and Engineering 367 (August 2020): 113115. http://dx.doi.org/10.1016/j.cma.2020.113115.

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23

Dupuy, Arnaud, Alfred Galichon, and Marc Henry. "Entropy methods for identifying hedonic models." Mathematics and Financial Economics 8, no. 4 (2014): 405–16. http://dx.doi.org/10.1007/s11579-014-0125-1.

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24

Wieser, Andreas. "Linnik’s problems and maximal entropy methods." Monatshefte für Mathematik 190, no. 1 (2019): 153–208. http://dx.doi.org/10.1007/s00605-019-01320-7.

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25

Prokopenko, Mikhail, and Carlos Gershenson. "Entropy Methods in Guided Self-Organisation." Entropy 16, no. 10 (2014): 5232–41. http://dx.doi.org/10.3390/e16105232.

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26

Chan, Jesse, David C. Del Rey Fernández, and Mark H. Carpenter. "Efficient Entropy Stable Gauss Collocation Methods." SIAM Journal on Scientific Computing 41, no. 5 (2019): A2938—A2966. http://dx.doi.org/10.1137/18m1209234.

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27

Silva, P. J. "Euclidean methods and the entropy function." Fortschritte der Physik 56, no. 7-9 (2008): 856–61. http://dx.doi.org/10.1002/prop.200810558.

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28

Gilmore, Christopher J. "Maximum entropy methods in electron crystallography." Microscopy Research and Technique 46, no. 2 (1999): 117–29. http://dx.doi.org/10.1002/(sici)1097-0029(19990715)46:2<117::aid-jemt5>3.0.co;2-q.

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29

Zhu, Zhongfan, Hongrui Wang, Bo Pang, Jie Dou, and Dingzhi Peng. "Comparison of Conventional Deterministic and Entropy-Based Methods for Predicting Sediment Concentration in Debris Flow." Water 11, no. 3 (2019): 439. http://dx.doi.org/10.3390/w11030439.

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In this study, the distribution of sediment concentration and the mean sediment concentration in debris flow were investigated using deterministic and probabilistic approaches. Tsallis entropy and Shannon entropy have recently been employed to estimate these parameters. However, other entropy theories, such as the general index entropy and Renyi entropy theories, which are generalizations of the Shannon entropy, have not been used to derive the sediment concentration in debris flow. Furthermore, no comprehensive and rigorous analysis has been conducted to compare the goodness of fit of existin

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30

Aguayo-Tapia, Sarahi, Gerardo Avalos-Almazan, and Jose de Jesus Rangel-Magdaleno. "Entropy-Based Methods for Motor Fault Detection: A Review." Entropy 26, no. 4 (2024): 299. http://dx.doi.org/10.3390/e26040299.

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In the signal analysis context, the entropy concept can characterize signal properties for detecting anomalies or non-representative behaviors in fiscal systems. In motor fault detection theory, entropy can measure disorder or uncertainty, aiding in detecting and classifying faults or abnormal operation conditions. This is especially relevant in industrial processes, where early motor fault detection can prevent progressive damage, operational interruptions, or potentially dangerous situations. The study of motor fault detection based on entropy theory holds significant academic relevance too,

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31

RINGHOFER, CHRISTIAN. "DISSIPATIVE DISCRETIZATION METHODS FOR APPROXIMATIONS TO THE BOLTZMANN EQUATION." Mathematical Models and Methods in Applied Sciences 11, no. 01 (2001): 133–48. http://dx.doi.org/10.1142/s0218202501000799.

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This paper deals with the spatial discretization of partial differential equations arising from Galerkin approximations to the Boltzmann equation, which preserves the entropy properties of the original collision operator. A general condition on finite difference methods is derived, which guarantees that the discrete system satisfies the appropriate equivalent of the entropy condition. As an application of this concept, entropy producing difference methods for the hydrodynamic model equations and for spherical harmonics expansions are presented.

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32

Zhao, Lina, Chengyu Liu, Shoushui Wei, Qin Shen, Fan Zhou, and Jianqing Li. "A New Entropy-Based Atrial Fibrillation Detection Method for Scanning Wearable ECG Recordings." Entropy 20, no. 12 (2018): 904. http://dx.doi.org/10.3390/e20120904.

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Entropy-based atrial fibrillation (AF) detectors have been applied for short-term electrocardiogram (ECG) analysis. However, existing methods suffer from several limitations. To enhance the performance of entropy-based AF detectors, we have developed a new entropy measure, named EntropyAF, which includes the following improvements: (1) use of a ranged function rather than the Chebyshev function to define vector distance, (2) use of a fuzzy function to determine vector similarity, (3) replacement of the probability estimation with density estimation for entropy calculation, (4) use of a flexibl

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33

Burik, N. A. "Methods for estimating entropy and analyzing sectoral development of the economy." Economics and Management 30, no. 4 (2024): 418–24. http://dx.doi.org/10.35854/1998-1627-2024-4-418-424.

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Aim. To substantiate the method of estimating the entropy of the sectoral structure of the economy and on this basis to develop methods of analyzing its sectoral development.Objectives. To define the essence of sectoral entropy of socio-economic systems; to consider the approaches to its assessment and the relationship between the entropy of industries and average per capita gross domestic product (GDP) with the structure of value added of industries of the economy.Methods. To achieve the set goals, the general scientific methods of analysis, synthesis, comparison, generalization, as well as m

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34

Kambarov, Ye Ye, G. K. Uazyrkhanova, M. Rutkowska-Gorczyca, and A. Ye Kussainov. "OVERVIEW OF THE HIGH-ENTROPY ALLOYS CONCEPT." NNC RK Bulletin, no. 1 (March 30, 2023): 25–39. http://dx.doi.org/10.52676/1729-7885-2023-1-25-39.

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The article presents a review of the results of research on high-entropy alloys, describing the principles of their formation, the basic concepts and properties of high-entropy alloys. The existing categories of the entropic alloys are listed. The effects resulting from the formation of high-entropy alloys are described: high entropy, lattice distortion, sluggish diffusion and cocktail effects. It is noted that the traditional thermodynamic representations for multicomponent alloys require additions. It is also noted that the application of Hume-Rothery rules to predict the phase composition o

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35

Cockburn, Bernardo. "Continuous dependence and error estimation for viscosity methods." Acta Numerica 12 (May 2003): 127–80. http://dx.doi.org/10.1017/s0962492902000107.

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In this paper, we review some ideas on continuous dependence results for the entropy solution of hyperbolic scalar conservation laws. They lead to a complete L^\infty(L^1)-approximation theory with which error estimates for numerical methods for this type of equation can be obtained. The approach we consider consists in obtaining continuous dependence results for the solutions of parabolic conservation laws and deducing from them the corresponding results for the entropy solution. This is a natural approach, as the entropy solution is nothing but the limit of solutions of parabolic scalar cons

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36

Butler, Keith T., Aron Walsh, Anthony K. Cheetham, and Gregor Kieslich. "Organised chaos: entropy in hybrid inorganic–organic systems and other materials." Chemical Science 7, no. 10 (2016): 6316–24. http://dx.doi.org/10.1039/c6sc02199a.

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Entropy is one of the fundamental quantities which links emerging research areas like flexibility and defect engineering in inorganic–organic hybrid materials. Here, we highlight the role of entropy in the past and discuss how computational methods can help us to understand entropic effects in inorganic–organic hybrid materials in the future.

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37

Gao, Lei, and Dong Han. "Methods of Moment and Maximum Entropy for Solving Nonlinear Expectation." Mathematics 7, no. 1 (2019): 45. http://dx.doi.org/10.3390/math7010045.

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In this paper, we consider a special nonlinear expectation problem on the special parameter space and give a necessary and sufficient condition for the existence of the solution. Meanwhile, we generalize the necessary and sufficient condition to the two-dimensional moment problem. Moreover, we use the maximum entropy method to carry out a kind of concrete solution and analyze the convergence for the maximum entropy solution. Numerical experiments are presented to compute the maximum entropy density functions.

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38

Zhang, Qi, Meizhu Li, and Yong Deng. "A new structure entropy of complex networks based on nonextensive statistical mechanics." International Journal of Modern Physics C 27, no. 10 (2016): 1650118. http://dx.doi.org/10.1142/s0129183116501187.

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The quantification of the complexity of network is a fundamental problem in the research of complex networks. There are many methods that have been proposed to solve this problem. Most of the existing methods are based on the Shannon entropy. In this paper, a new method which is based on the nonextensive statistical mechanics is proposed to quantify the complexity of complex network. On the other hand, most of the existing methods are based on a single structure factor, such as the degree of each node or the betweenness of each node. In the proposed method, both of the influence of the degree

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39

Bieszk-Stolorz, Beata. "Entropy in the Assessment of the Labour Market Situation in the Context of the Survival Analysis Methods." Entropy 27, no. 7 (2025): 665. https://doi.org/10.3390/e27070665.

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Since Shannon’s pioneering work, the concept of entropy has been used in many major scientific fields. It is therefore a universal concept but also defined in different ways. Entropy is used in studies of system complexity and to investigate the information content of probability distributions. One of the areas of its applications is human lifespan, i.e., the link between entropy and the methods of survival analysis. These methods are also used in assessing the duration of any socio-economic phenomenon. The aim of this article is to assess the market situation on the basis of the entropy of du

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40

Bajkova, A. T. "VLBI Image Deconvolution Based on Generalized Nonlinear Information Methods." International Astronomical Union Colloquium 164 (1998): 409–10. http://dx.doi.org/10.1017/s0252921100046170.

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AbstractA number of nonlinear image deconvolution procedures based on extremizing generalized Shannon entropy, Kullback-Leibler cross-entropy and Renyi information measures are suggested for VLBI mapping with minimal nonlinear distortions. A new approach to phaseless mapping urgent in the case of unreliable closure phases is proposed.

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41

Berestneva, O. G., Ya S. Pekker, and S. S. Murzina. "ENTROPY METHODS IN ANALYSIS OF BIOLOGICAL SYSTEMS." Bulletin of Siberian Medicine 13, no. 4 (2014): 15–20. http://dx.doi.org/10.20538/1682-0363-2014-4-15-20.

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The adaptation of people to new production environment are often influenced by very unusual, excessive and harsh environmental factors, genetically inadequate to its nature. Human adaptation to the new production conditions can be summarized as a set of social and biological properties and characteristics needed to sustain the existence of the human body in a particular ecological environment.It is necessary under the new conditions to achieve harmony of human interaction with the physical environment of their lives, adequate human nature. In addressing this fundamental problem of the primary

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42

Piantadosi, Julia, Phil Howlett, Jonathan Borwein, and John Henstridge. "Maximum entropy methods for generating simulated rainfall." Numerical Algebra, Control and Optimization 2, no. 2 (2012): 233–56. http://dx.doi.org/10.3934/naco.2012.2.233.

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43

Waldrip, Steven H., and Robert K. Niven. "Maximum Entropy Derivation of Quasi-Newton Methods." SIAM Journal on Optimization 26, no. 4 (2016): 2495–511. http://dx.doi.org/10.1137/15m1027668.

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44

Mosinoiu, Laurentiu Florin, Ioana Cristina Badea, Anca Elena Sobetkii, et al. "High entropy alloys and methods for synthesis." MATEC Web of Conferences 401 (2024): 14002. http://dx.doi.org/10.1051/matecconf/202440114002.

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High entropy alloys (HEA) are now a well-known group of materials, which has been studied intensely in the past decade. Due to the high complexity of the various HEA structures and the wide compositional spectrum, the research in the field continues with important discoveries and high work volume. Numerous articles presented various modalities to describe the thermodynamics and atomic arrangement in HEA structures and develop specific criteria for the selection of compositions with predicted solid solution structures. The next step towards the industrial use of the new category of alloys needs

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45

Pranzetti, Daniele, and Hanno Sahlmann. "Horizon entropy with loop quantum gravity methods." Physics Letters B 746 (June 2015): 209–16. http://dx.doi.org/10.1016/j.physletb.2015.04.070.

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46

Golan, Amos, and Esfandiar Maasoumi. "Information Theoretic and Entropy Methods: An Overview." Econometric Reviews 27, no. 4-6 (2008): 317–28. http://dx.doi.org/10.1080/07474930801959685.

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47

Jani, Mehul, and Rajeev K. Azad. "Information entropy based methods for genome comparison." ACM SIGBioinformatics Record 3, no. 2 (2013): 1–4. http://dx.doi.org/10.1145/2500124.2500126.

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Brownlee, R. A., A. N. Gorban, and J. Levesley. "Nonequilibrium entropy limiters in lattice Boltzmann methods." Physica A: Statistical Mechanics and its Applications 387, no. 2-3 (2008): 385–406. http://dx.doi.org/10.1016/j.physa.2007.09.031.

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de Sá, Cláudio Rebelo, Carlos Soares, and Arno Knobbe. "Entropy-based discretization methods for ranking data." Information Sciences 329 (February 2016): 921–36. http://dx.doi.org/10.1016/j.ins.2015.04.022.

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50

Greco, F., L. Coox, and W. Desmet. "Maximum-entropy methods for time-harmonic acoustics." Computer Methods in Applied Mechanics and Engineering 306 (July 2016): 1–18. http://dx.doi.org/10.1016/j.cma.2016.03.047.

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