scholarly journals A Dynamic Network Model to Measure Exposure Diversification in the Austrian Interbank Market

2020 ◽  
Author(s):  
Juraj Hledik ◽  
Riccardo Rastelli
Keyword(s):  
Network Model ◽  
Dynamic Network ◽  
Interbank Market ◽  
Dynamic Network Model

Dynamic Network Model Analysis Based on Communication Network

2014 ◽  
Vol 989-994 ◽  
pp. 2639-2642
Author(s):  
Nan Qi Yuan ◽  
Tian Jiang ◽  
Shi Bai ◽  
Hao Sun ◽  
Jing Mei Zhao
Keyword(s):  
Communication Network ◽  
Convergence Rate ◽  
Network Model ◽  
Dynamic Network ◽  
Model Analysis ◽  
Vicsek Model ◽  
Dynamic Network Model ◽  
Weighted Model

In order to research dynamic network astringency reaching uniformity, this paper perfects the Vicsek model and puts forward improving dynamic network astringency efficiency by weighted model. We prove that the convergence rate of weighted model is faster than the classic Vicsek model and it can optimize dynamic network.

scholarly journals SIS dynamic network model based on product semantics from the perspective of infectious disease dynamics

2021 ◽  
Vol 235 ◽  
pp. 03035
Author(s):  
jiaojiao Lv ◽  
yingsi Zhao
Keyword(s):  
Network Model ◽  
Purchase Intention ◽  
Recommendation System ◽  
Optimal Algorithm ◽  
Dynamic Network ◽  
Distribution Model ◽  
Recommendation Algorithm ◽  
Model Based ◽  
Dynamic Network Model ◽  
Recommendation Algorithms

Recommendation system is unable to achive the optimal algorithm, recommendation system precision problem into bottleneck. Based on the perspective of product marketing, paper takes the inherent attribute as the classification standard and focuses on the core problem of “matching of product classification and recommendation algorithm of users’ purchase demand”. Three hypotheses are proposed: (1) inherent attributes of the product directly affect user demand; (2) classified product is suitable for different recommendation algorithms; (3) recommendation algorithm integration can achieve personalized customization. Based on empirical research on the relationship between characteristics of recommendation information (independent variable) and purchase intention (dependent variable), it is concluded that predictability and difference of recommendation information are not fully perceived and stimulation is insufficient. Therefore, SIS dynamic network model based on the distribution model of SIS virus is constructed. It discusses the spreading path of recommendation information and “infection” situation of consumers to enhance accurate matching of recommendation system.

scholarly journals Oscillating epidemics in a dynamic network model: stochastic and mean-field analysis

2015 ◽  
Vol 72 (5) ◽  
pp. 1153-1176 ◽  
Author(s):  
András Szabó-Solticzky ◽  
Luc Berthouze ◽  
Istvan Z. Kiss ◽  
Péter L. Simon
Keyword(s):  
Network Model ◽  
Mean Field ◽  
Dynamic Network ◽  
Field Analysis ◽  
Dynamic Network Model
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