scholarly journals Global Convergence Analysis of the Flower Pollination Algorithm: A Discrete-Time Markov Chain Approach

2017 ◽  
Vol 108 ◽  
pp. 1354-1363 ◽  
Author(s):  
Xingshi He ◽  
Xin-She Yang ◽  
Mehmet Karamanoglu ◽  
Yuxin Zhao
Keyword(s):  
Markov Chain ◽  
Global Convergence ◽  
Convergence Analysis ◽  
Discrete Time ◽  
Flower Pollination Algorithm ◽  
Discrete Time Markov Chain ◽  
Flower Pollination ◽  
Markov Chain Approach ◽  
Global Convergence Analysis

scholarly journals Discrete-time Markov chain approach to contact-based disease spreading in complex networks

2010 ◽  
Vol 89 (3) ◽  
pp. 38009 ◽  
Author(s):  
S. Gómez ◽  
A. Arenas ◽  
J. Borge-Holthoefer ◽  
S. Meloni ◽  
Y. Moreno
Keyword(s):  
Markov Chain ◽  
Complex Networks ◽  
Discrete Time ◽  
Discrete Time Markov Chain ◽  
Markov Chain Approach ◽  
Disease Spreading

scholarly journals Financial Risk Information Spreading on Metapopulation Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Min Lin ◽  
Li Duan
Keyword(s):  
Markov Chain ◽  
Discrete Time ◽  
Financial Risk ◽  
Transmission Probability ◽  
Risk Information ◽  
Discrete Time Markov Chain ◽  
Markov Chain Approach ◽  
Spreading Dynamics ◽  
Information Spreading ◽  
And Migration

The financial risk information diffuses through various kinds of social networks, such as Twitter and Facebook. Individuals transmit the financial risk information which can migrate among different platforms or forums. In this paper, we propose a financial risk information spreading model on metapopulation networks. The subpopulation represents a platform or forum, and individuals migrate among them to transmit the information. We use a discrete-time Markov chain approach to describe the spreading dynamics’ evolution and deduce the outbreak threshold point. We perform numerical simulation on artificial networks and discover that the financial risk information can be promoted once increasing the information transmission probability and active subpopulation fraction. The weight variance and migration probability cannot significantly affect the financial risk spreading size. The discrete-time Markov chain approach can reasonably predict the above phenomena.

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