Fractional-order modeling and optimal control of a new online game addiction model based on real data

Guo, Youming; Li, Tingting

doi:10.1016/j.cnsns.2023.107221

Cited by 27 publications

(3 citation statements)

References 36 publications

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“…Compared with the control efect of the biological virus COVID-19, Li and Guo [42] analyzed the optimal control and efectiveness of the novel COVID-19 model of the Omicron strain. Guo and Li [43] conducted fractional-order modeling and optimal control of a new online game addiction model based on real data. Te above work has a good enlightening signifcance for us to carry out the control of network viruses.…”

Section: Introductionmentioning

confidence: 99%

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Tang,

Yang,

2024

International Journal of Intelligent Systems

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The proliferation of computer viruses has escalated in recent years, posing threats not only to individuals’ safety and property but also to societal well-being. Consequently, effectively curtailing virus spread has become an urgent imperative. To address this issue, our paper introduces a new virus propagation model and associated control strategy. First, diverging from conventional approaches in network virus literature, we propose a susceptible-latent-breaking-out-recovered-susceptible (SLBRS) virus propagation model tailored to the topological characteristics of scale-free networks, thus comprehensively incorporating network structure’s impact on virus propagation. Second, we analyze the model’s foundational properties, derive the basic reproduction number, and demonstrate the existence and global asymptotic stability of disease-free equilibrium. Finally, leveraging global stability of the model at the disease-free equilibrium, we integrate the target immunization strategy (TIS) and the acquaintance immunization strategy (AIS) to devise an optimal control strategy. The paper’s findings offer fresh insights into disease-free equilibrium existence and stability, furnishing a more dependable approach to curbing network virus dissemination. The simulation results demonstrate the persistent presence of network viruses in the absence of control measures and the instability of the disease-free equilibrium. However, effective control is achieved after implementing immunization measures.

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Section: Introductionmentioning

confidence: 99%

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Tang,

Yang,

2024

International Journal of Intelligent Systems

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“…Mathematical modeling is applied to study the prevention of infectious disease dynamics and plays an important scientific contribution [33][34][35][36][37]. The infectious disease dynamics model has been used by many researchers to study addictions to gaming, alcohol, drugs, and social media, depression, and other issues [38][39][40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling, analysis and numerical simulation of social media addiction and depression

Ali,

Javeed,

Faiz

et al. 2024

PLoS ONE

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We formulate a mathematical model of social media addiction and depression (SMAD) in this study. Key aspects, such as social media addiction and depression disease-free equilibrium point (SMADDFEP), social media addiction and depression endemic equilibrium point (SMADEEP), and basic reproduction number (R0), have been analyzed qualitatively. The results indicate that if R0 < 1, the SMADDFEP is locally asymptotically stable. The global asymptotic stability of the SMADDFEP has been established using the Castillo-Chavez theorem. On the other hand, if R0 > 1, the unique endemic equilibrium point (SMADEEP) is locally asymptotically stable by Lyapunov theorem, and the model exhibits a forward bifurcation at R0 = 1 according to the Center Manifold theorem. To examine the model’s sensitivity, we calculated the normalized forward sensitivity index and conducted a Partial Rank Correlation Coefficient (PRCC) analysis to describe the influence of parameters on the SMAD. The numerical results obtained using the Fourth-order Runge-Kutta (RK-4) scheme show that increasing the number of addicted individuals leads to an increase in the number of depressed individuals.

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“…This class of methods can effectively solve the problem of parameter estimation and is widely used in various fields. Besides, some parameter estimation methods have been used to model the spread of infectious diseases, including online game addiction [34,35], COVID-19 [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Improved artificial gorilla troops optimizer with chaotic adaptive parameters - application to the parameter estimation problem of mixed additive and multiplicative random error models

Wang,

Han,

Pang

2023

Meas. Sci. Technol.

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For mixed additive and multiplicative random error models (MAM models), due to the complex correlation between the parameters and the model power array, derivative operations will be inevitable in the actual calculation. When the observation equation is in nonlinear form, the operations will be more complicated. The swarm intelligence optimization algorithm (SIO) can effectively solve the derivative problem when estimating the nonlinear model parameters using conventional iterative algorithms. However, for different problems, the conventional SIO cannot effectively balance the ability of global and local behavior, resulting in the algorithm falling into prematureness and failing to output effective parameter information. To address the above problems, the improved artificial gorilla troops optimizer (CAGTO) algorithm with chaotic adaptive behavior is proposed. To address the problem that the population generated by the algorithm using pseudo-random numbers in the initialization population phase has poor traversability in the feasible domain, the chaotic sequence is applied to initialize the population instead of pseudo-random number generation to ensure that the population can traverse the feasible domain as much as possible and improve the global search capability of the algorithm. Adaptive parameters that vary linearly and nonlinearly with the algorithm process are constructed to balance the global search and local search ability, while accelerating the convergence speed. Two CAGTO algorithms with different parameter settings are constructed for different problems, and the experimental results show that both CAGTO algorithms can effectively solve the parameter estimation problem of MAM models with different nonlinear forms of observation equations compared with several other comparative algorithms.

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Fractional-order modeling and optimal control of a new online game addiction model based on real data

Cited by 27 publications

References 36 publications

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Dynamics and Control Strategies for SLBRS Model of Computer Viruses Based on Complex Networks

Mathematical modelling, analysis and numerical simulation of social media addiction and depression

Improved artificial gorilla troops optimizer with chaotic adaptive parameters - application to the parameter estimation problem of mixed additive and multiplicative random error models

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