Literature DB >> 33333930

A Survey of Information Entropy Metrics for Complex Networks.

Yamila M Omar1, Peter Plapper1.   

Abstract

Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts.

Entities:  

Keywords:  Shanon’s entropy; centrality; complex networks; entropy

Year:  2020        PMID: 33333930     DOI: 10.3390/e22121417

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  3 in total

1.  Brain information processing capacity modeling.

Authors:  Tongtong Li; Yu Zheng; Zhe Wang; David C Zhu; Jian Ren; Taosheng Liu; Karl Friston
Journal:  Sci Rep       Date:  2022-02-09       Impact factor: 4.379

2.  Identifying Influential Nodes in Complex Networks Based on Multiple Local Attributes and Information Entropy.

Authors:  Jinhua Zhang; Qishan Zhang; Ling Wu; Jinxin Zhang
Journal:  Entropy (Basel)       Date:  2022-02-18       Impact factor: 2.524

3.  Capture and Prediction of Rainfall-Induced Landslide Warning Signals Using an Attention-Based Temporal Convolutional Neural Network and Entropy Weight Methods.

Authors:  Di Zhang; Kai Wei; Yi Yao; Jiacheng Yang; Guolong Zheng; Qing Li
Journal:  Sensors (Basel)       Date:  2022-08-19       Impact factor: 3.847

  3 in total

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