Results 1 to 10 of about 3,668 (97)

Asymptotic Normality for Plug-In Estimators of Generalized Shannon’s Entropy [PDF]

Entropy, 2022
Shannon’s entropy is one of the building blocks of information theory and an essential aspect of Machine Learning (ML) methods (e.g., Random Forests).
Jialin Zhang, Jingyi Shi
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Ranking DMUs by Combining Cross-Efficiency Scores Based on Shannon’s Entropy [PDF]

Entropy, 2019
Cross-efficiency evaluation is an effective approach for ranking decision-making units (DMUs), and there exist different perspectives from different cross-efficiency evaluation models.
Yueh-Chiang Lee
doaj   +2 more sources

Information Theory Meets Quantum Chemistry: A Review and Perspective [PDF]

Entropy
In this survey, we begin with a concise introduction to information theory within Shannon’s framework, focusing on the key concept of Shannon entropy and its related quantities: relative entropy, joint entropy, conditional entropy, and mutual information.
Yilin Zhao, Dongbo Zhao, Chunying Rong, Shubin Liu, Paul W. Ayers   +4 more
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On distance-based topological indices and co-indices of fractal-type molecular graphs and their respective graph entropies.

PLoS ONE, 2023
In graph theory, a topological index is a numerical value that is in good correlation with certain physical properties of a molecule. It serves as an indicator of how a chemical structure behaves. The Shannon's entropy describes a comparable loss of data
Mehar Ali Malik, Muhammad Imran, Muhammad Adeel   +2 more
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Fisher and Shannon Functionals for Hyperbolic Diffusion

Entropy, 2023
The complexity measure for the distribution in space-time of a finite-velocity diffusion process is calculated. Numerical results are presented for the calculation of Fisher’s information, Shannon’s entropy, and the Cramér–Rao inequality, all of which ...
Manuel O. Cáceres, Marco Nizama, Flavia Pennini   +2 more
doaj   +1 more source

An Entropy Measure of Non-Stationary Processes

Entropy, 2014
Shannon’s source entropy formula is not appropriate to measure the uncertainty of non-stationary processes. In this paper, we propose a new entropy measure for non-stationary processes, which is greater than or equal to Shannon’s source entropy.
Ling Feng Liu, Han Ping Hu, Ya Shuang Deng, Nai Da Ding   +3 more
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A Comparative Study of Frequency Ratio, Shannon’s Entropy and Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility Assessment

ISPRS International Journal of Geo-Information, 2021
Landslide susceptibility maps are very important tools in the planning and management of landslide prone areas. Qualitative and quantitative methods each have their own advantages and dis-advantages in landslide susceptibility mapping.
Sandeep Panchal, Amit K. Shrivastava
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Permutation Entropy for Random Binary Sequences

Entropy, 2015
In this paper, we generalize the permutation entropy (PE) measure to binary sequences, which is based on Shannon’s entropy, and theoretically analyze this measure for random binary sequences.
Lingfeng Liu, Suoxia Miao, Mengfan Cheng, Xiaojing Gao   +3 more
doaj   +1 more source

Characterization of avoided crossings in acoustic superlattices: The Shannon entropy in acoustics

Frontiers in Physics, 2022
We show that Shannon’s information entropy provides a correct physical insight of localization effects taking place in structured fields fashioned by eigenmodes upon substrate.
José Sánchez-Dehesa, J. Ricardo Arias-Gonzalez   +1 more
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Entropy and Information Approaches to Genetic Diversity and its Expression: Genomic Geography

Entropy, 2010
This article highlights advantages of entropy-based genetic diversity measures, at levels from gene expression to landscapes. Shannon’s entropy-based diversity is the standard for ecological communities.
William B. Sherwin
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