A Complex Network Epidemiological Approach for Infectious Disease Spread Control with Time-Varying Connections

被引：0
|
作者：
Alanis, Alma Y. [1 ]
Munoz-Gomez, Gustavo [2 ]
Ramirez, Nancy F. [3 ]
Sanchez, Oscar D. [1 ]
Alvarez, Jesus G. [1 ]
机构：
[1] Univ Guadalajara, CUCEI Univ Ctr Exact Sci & Engn, Guadalajara 44430, Mexico
[2] Tecnol Nacl Mexico, Campus Nochistlan, Nochistlan 99900, Mexico
[3] Univ Guadalajara, CUCSUR Univ Ctr South Coast, Guadalajara 44100, Mexico
来源：
ALGORITHMS | 2024年 / 17卷 / 12期
关键词：
neural identifier; impulsive control; infectious diseases; pinning control; complex dynamical networks; PULSE VACCINATION; CONSTANT; MODELS;
D O I：
10.3390/a17120577
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This work introduces an impulsive neural control algorithm designed to mitigate the spread of epidemic diseases. The objective of this paper is the development of a vaccination strategy based on a PIN-type impulsive controller based on an online-trained neural identifier to control the spread of infectious diseases under a complex network approach with time-varying connections where each node represents a population of individuals whose dynamics are defined by the MSEIR epidemiological model. Considering an unknown model of the system, a neural identifier is designed that provides a nonlinear model for the complex network trained through an extended Kalman filter algorithm. Simulation results are presented by applying the proposed control scheme for a complex network parameterized as infectious diseases.
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页数：15
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