Results 11 to 20 of about 3,787 (215)

Entropic Statistics: Concept, Estimation, and Application in Machine Learning and Knowledge Extraction

open access: yesMachine Learning and Knowledge Extraction, 2022
The demands for machine learning and knowledge extraction methods have been booming due to the unprecedented surge in data volume and data quality. Nevertheless, challenges arise amid the emerging data complexity as significant chunks of information and ...
Jialin Zhang
doaj   +1 more source

Imprecise Shannon’s Entropy and Multi Attribute Decision Making

open access: yesEntropy, 2010
Finding the appropriate weight for each criterion is one of the main points in Multi Attribute Decision Making (MADM) problems. Shannon’s entropy method is one of the various methods for finding weights discussed in the literature.
Reza Fallahnejad   +1 more
doaj   +1 more source

On Entropy of Some Fractal Structures

open access: yesFractal and Fractional, 2023
Shannon entropy, also known as information entropy or entropy, measures the uncertainty or randomness of probability distribution. Entropy is measured in bits, quantifying the average amount of information required to identify an event from the ...
Haleemah Ghazwani   +3 more
doaj   +1 more source

Assessment of urban sprawl using Shannon’s entropy and fractal analysis: a case study of Atakum, Ilkadim and Canik (Samsun, Turkey)

open access: yesJournal of Environmental Engineering and Landscape Management, 2017
Urban sprawl is one of the most important problems in urban development due to its negative environmental and societal impacts. Therefore, the spatial pattern of urban growth should be accurately analyzed and well understood for effective urban planning.
Derya Ozturk
doaj   +1 more source

AN IMPROVED METHODOLOGY FOR MULTI-CRITERIA EVALUATIONS IN THE SHIPPING INDUSTRY

open access: yesBrodogradnja, 2016
This paper presents a reliable, easy and more objective approach for ranking and determining preference in a multi-criteria decision-making problem within the shipping industry.
Daniel Osezua Aikhuele   +1 more
doaj   +1 more source

A Suggestion of Converting Protein Intrinsic Disorder to Structural Entropy Using Shannon’s Information Theory

open access: yesEntropy, 2019
We propose a framework to convert the protein intrinsic disorder content to structural entropy (H) using Shannon’s information theory (IT). The structural capacity (C), which is the sum of H and structural information (I), is equal to the amino acid ...
Hao-Bo Guo   +5 more
doaj   +1 more source

Identifying and Ranking Factors Affecting Earnings Response Coefficient [PDF]

open access: yesIranian Journal of Accounting, Auditing & Finance, 2022
One of the most critical questions after financial statements is why market responses differ from companies with almost similar statements. This research aims to answer this question by identifying factors affecting the earnings response coefficient.
Seyed Mohsen Mousavi   +4 more
doaj   +1 more source

Geometric Partition Entropy: Coarse-Graining a Continuous State Space

open access: yesEntropy, 2022
Entropy is re-examined as a quantification of ignorance in the predictability of a one dimensional continuous phenomenon. Although traditional estimators for entropy have been widely utilized in this context, we show that both the thermodynamic and ...
Christopher Tyler Diggans   +1 more
doaj   +1 more source

Shannon Entropy Used for Feature Extractions of Optical Patterns in the Context of Structural Health Monitoring

open access: yesEntropy, 2023
A novelty signal processing method is proposed for a technical vision system (TVS). During data acquisition of an optoelectrical signal, part of this is random electrical fluctuation of voltages.
Wendy Garcia-González   +5 more
doaj   +1 more source

An Assessment of Hermite Function Based Approximations of Mutual Information Applied to Independent Component Analysis

open access: yesEntropy, 2008
At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation.
Julian Sorensen
doaj   +1 more source

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