Yutao Yan, Shuzhen Yu, Zhiyong Yu, Haijun Jiang, Hui Wang
{"title":"具有多平台交叉传播机制的延迟离散SEIR负信息传播模型的全局动力学","authors":"Yutao Yan, Shuzhen Yu, Zhiyong Yu, Haijun Jiang, Hui Wang","doi":"10.1016/j.cnsns.2025.108591","DOIUrl":null,"url":null,"abstract":"Taking into account the phenomenon of cross-platform propagation of network information and multi-platform network environments, this paper constructs two discrete-time negative information propagation models with time delays. For the single platform model, we first prove that the information-free equilibrium (IFE) is locally asymptotically stable (LA-stable) and globally asymptotically stable (GA-stable) when <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mrow><mml:msub><mml:mrow><mml:mi>ℛ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\"><</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>. Then, by using the method of Lyapunov function, it is obtained that when <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mrow><mml:msub><mml:mrow><mml:mi>ℛ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">></mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>, the information-spreading equilibrium (ISE) is GA-stable. For the multi-platform model, it is found that its dynamic behaviors are completely determined by the propagation threshold <mml:math altimg=\"si3.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mover accent=\"true\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>. To be specific, the IFE of the multi-platform model is GA-stable when <mml:math altimg=\"si4.svg\" display=\"inline\"><mml:mrow><mml:msub><mml:mrow><mml:mover accent=\"true\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\"><</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>. With respect to <mml:math altimg=\"si5.svg\" display=\"inline\"><mml:mrow><mml:msub><mml:mrow><mml:mover accent=\"true\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">></mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>, it is proved that the ISE is GA-stable by using graph theory approach. The numerical experiments verify the accuracy of the conclusions. In the end, a real case is selected to illustrate the applicability of the model.","PeriodicalId":50658,"journal":{"name":"Communications in Nonlinear Science and Numerical Simulation","volume":"7 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global dynamics of delayed discrete-time SEIR negative information propagation model with multi-platform and cross-transmission mechanism\",\"authors\":\"Yutao Yan, Shuzhen Yu, Zhiyong Yu, Haijun Jiang, Hui Wang\",\"doi\":\"10.1016/j.cnsns.2025.108591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Taking into account the phenomenon of cross-platform propagation of network information and multi-platform network environments, this paper constructs two discrete-time negative information propagation models with time delays. For the single platform model, we first prove that the information-free equilibrium (IFE) is locally asymptotically stable (LA-stable) and globally asymptotically stable (GA-stable) when <mml:math altimg=\\\"si1.svg\\\" display=\\\"inline\\\"><mml:mrow><mml:msub><mml:mrow><mml:mi>ℛ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\\\"goodbreak\\\" linebreakstyle=\\\"after\\\"><</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>. Then, by using the method of Lyapunov function, it is obtained that when <mml:math altimg=\\\"si2.svg\\\" display=\\\"inline\\\"><mml:mrow><mml:msub><mml:mrow><mml:mi>ℛ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\\\"goodbreak\\\" linebreakstyle=\\\"after\\\">></mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>, the information-spreading equilibrium (ISE) is GA-stable. For the multi-platform model, it is found that its dynamic behaviors are completely determined by the propagation threshold <mml:math altimg=\\\"si3.svg\\\" display=\\\"inline\\\"><mml:msub><mml:mrow><mml:mover accent=\\\"true\\\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>. To be specific, the IFE of the multi-platform model is GA-stable when <mml:math altimg=\\\"si4.svg\\\" display=\\\"inline\\\"><mml:mrow><mml:msub><mml:mrow><mml:mover accent=\\\"true\\\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\\\"goodbreak\\\" linebreakstyle=\\\"after\\\"><</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>. With respect to <mml:math altimg=\\\"si5.svg\\\" display=\\\"inline\\\"><mml:mrow><mml:msub><mml:mrow><mml:mover accent=\\\"true\\\"><mml:mrow><mml:mi>ℜ</mml:mi></mml:mrow><mml:mrow><mml:mo>ˆ</mml:mo></mml:mrow></mml:mover></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub><mml:mo linebreak=\\\"goodbreak\\\" linebreakstyle=\\\"after\\\">></mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math>, it is proved that the ISE is GA-stable by using graph theory approach. The numerical experiments verify the accuracy of the conclusions. In the end, a real case is selected to illustrate the applicability of the model.\",\"PeriodicalId\":50658,\"journal\":{\"name\":\"Communications in Nonlinear Science and Numerical Simulation\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-01-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Nonlinear Science and Numerical Simulation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cnsns.2025.108591\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Nonlinear Science and Numerical Simulation","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1016/j.cnsns.2025.108591","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Global dynamics of delayed discrete-time SEIR negative information propagation model with multi-platform and cross-transmission mechanism
Taking into account the phenomenon of cross-platform propagation of network information and multi-platform network environments, this paper constructs two discrete-time negative information propagation models with time delays. For the single platform model, we first prove that the information-free equilibrium (IFE) is locally asymptotically stable (LA-stable) and globally asymptotically stable (GA-stable) when ℛ0<1. Then, by using the method of Lyapunov function, it is obtained that when ℛ0>1, the information-spreading equilibrium (ISE) is GA-stable. For the multi-platform model, it is found that its dynamic behaviors are completely determined by the propagation threshold ℜˆ0. To be specific, the IFE of the multi-platform model is GA-stable when ℜˆ0<1. With respect to ℜˆ0>1, it is proved that the ISE is GA-stable by using graph theory approach. The numerical experiments verify the accuracy of the conclusions. In the end, a real case is selected to illustrate the applicability of the model.
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The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity.
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Topics of interest:
Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity.
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