Entropy | An Open Access Journal from MDPI
Entropy is an international and interdisciplinary peer-reviewed open access journal of entropy and information studies, published monthly online by MDPI.
About Entropy - MDPI
Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details.
Entropy - MDPI
The concept of entropy constitutes, together with energy, a cornerstone of contemporary physics and related areas. It was originally introduced by Clausius in 1865 along abstract lines focusing on thermodynamical irreversibility of macroscopic physical processes.
Entropy | Instructions for Authors - MDPI
Manuscripts for Entropy should be submitted online at susy.mdpi.com. The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process.
Entropy | Special Issues - MDPI
Entropy publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions.
Approximate Entropy and Sample Entropy: A Comprehensive …
2019年5月28日 · Approximate Entropy and Sample Entropy are two algorithms for determining the regularity of series of data based on the existence of patterns. Despite their similarities, the theoretical ideas behind those techniques are different but usually ignored.
A Brief Review of Generalized Entropies - MDPI
Abstract. Entropy appears in many contexts (thermodynamics, statistical mechanics, information theory, measure-preserving dynamical systems, topological dynamics, etc.) as a measure of different properties (energy that cannot produce work, disorder, uncertainty, randomness, complexity, etc.).
Information Entropy in Chemistry: An Overview - MDPI
2021年9月23日 · Recent advances in the mentioned areas make information entropy a central concept in interdisciplinary studies on digitalizing chemical reactions, chemico-information synthesis, crystal engineering, as well as digitally rethinking basic notions of structural chemistry in terms of informatics.
Entropy: From Thermodynamics to Information Processing - MDPI
2021年10月14日 · Using Kullback–Leibler Divergence to Obtain an Analogous of the Second Law of Thermodynamics. Today, modern supervised machine learning techniques use extensively a measure formulated using the Kullback–Leibler divergence as a cost function when training classifiers, the cross-entropy.
Applied Sciences | An Open Access Journal from MDPI
In this study, the efficiency of logistics operations in 118 countries was evaluated using an integrated multi-criteria decision-making (MCDM) model objectively weighted by the Entropy method. Countries were ranked using the MCRAT, SAW, TOPSIS, and FUCA methods.