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Добірка наукової літератури з теми "NONLINEAR INCIDENCE RATES"

Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "NONLINEAR INCIDENCE RATES"

1

Liu, Wei-min, Herbert W. Hethcote, and Simon A. Levin. "Dynamical behavior of epidemiological models with nonlinear incidence rates." Journal of Mathematical Biology 25, no. 4 (September 1987): 359–80. http://dx.doi.org/10.1007/bf00277162.

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2

Hui, Jing, and Lansun Chen. "Impulsive vaccination of sir epidemic models with nonlinear incidence rates." Discrete & Continuous Dynamical Systems - B 4, no. 3 (2004): 595–605. http://dx.doi.org/10.3934/dcdsb.2004.4.595.

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3

Mukherjee, D., J. Chattopadhyay, and P. K. Tapaswi. "Global stability results of epidemiological models with nonlinear incidence rates." Mathematical and Computer Modelling 18, no. 2 (July 1993): 89–92. http://dx.doi.org/10.1016/0895-7177(93)90009-n.

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4

Ponciano, José M., and Marcos A. Capistrán. "First Principles Modeling of Nonlinear Incidence Rates in Seasonal Epidemics." PLoS Computational Biology 7, no. 2 (February 17, 2011): e1001079. http://dx.doi.org/10.1371/journal.pcbi.1001079.

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5

Sachs, Dominik, Aleh Tsyvinski, and Nicolas Werquin. "Nonlinear Tax Incidence and Optimal Taxation in General Equilibrium." Econometrica 88, no. 2 (2020): 469–93. http://dx.doi.org/10.3982/ecta14681.

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Анотація:
We study the incidence of nonlinear labor income taxes in an economy with a continuum of endogenous wages. We derive in closed form the effects of reforming nonlinearly an arbitrary tax system, by showing that this problem can be formalized as an integral equation. Our tax incidence formulas are valid both when the underlying assignment of skills to tasks is fixed or endogenous. We show qualitatively and quantitatively that contrary to conventional wisdom, if the tax system is initially suboptimal and progressive, the general‐equilibrium “trickle‐down” forces may raise the benefits of increasing the marginal tax rates on high incomes. We finally derive a parsimonious characterization of optimal taxes.
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6

Rohith, G., and K. B. Devika. "Dynamics and control of COVID-19 pandemic with nonlinear incidence rates." Nonlinear Dynamics 101, no. 3 (June 25, 2020): 2013–26. http://dx.doi.org/10.1007/s11071-020-05774-5.

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7

Liu, Yicheng, Yimin Du, and Jianhong Wu. "Backward/Hopf bifurcations in SIS models with delayed nonlinear incidence rates." Frontiers of Mathematics in China 3, no. 4 (October 23, 2008): 535–53. http://dx.doi.org/10.1007/s11464-008-0040-y.

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8

Li, Li, Gui-Quan Sun, and Zhen Jin. "Bifurcation and chaos in an epidemic model with nonlinear incidence rates." Applied Mathematics and Computation 216, no. 4 (April 2010): 1226–34. http://dx.doi.org/10.1016/j.amc.2010.02.014.

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9

Yuan, Zhaohui, and Lin Wang. "Global stability of epidemiological models with group mixing and nonlinear incidence rates." Nonlinear Analysis: Real World Applications 11, no. 2 (April 2010): 995–1004. http://dx.doi.org/10.1016/j.nonrwa.2009.01.040.

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10

Lu, Zhonghua, Xianning Liu, and Lansun Chen. "Hopf bifurcation of nonlinear incidence rates SIR epidemiological models with stage structure." Communications in Nonlinear Science and Numerical Simulation 6, no. 4 (December 2001): 205–9. http://dx.doi.org/10.1016/s1007-5704(01)90015-2.

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Більше джерел

Дисертації з теми "NONLINEAR INCIDENCE RATES"

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KAI, TSUI CHIH, and 崔智凱. "On the dynamics of an SEIR model with nonlinear incidence rates." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/38799381090658710564.

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Анотація:
碩士
東吳大學
數學系
101
An SEIR epidemic model with non-linear incidence rates, is considered in this thesis. The dynamical behaviors are determined by the basic reproduction number R0 and p, q. If R0 1, q=1 and p>1, the trivial equilibrium is globally asymptotically stable. For all R0>0, (i) q=1 and 0
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2

KUMAR, ABHISHEK. "MATHEMATICAL MODELING IN EPIDEMIOLOGY." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16918.

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Анотація:
In the present thesis, various aspects of the transmission dynamics of epidemics are discussed through the mathematical models. We have proposed and analyzed the various mathematical models to control the spread of emerging/ re-emerging epidemics. We have investigated the facts and reasons behind the spread and control of infectious diseases/ epidemics. After analyzing several systems, various results obtained by analysis of the problem are discussed. The mathematical models have been analyzed for positiveness, boundedness, and stability. Locals stability, global stability, Routh-Hurwitz stability criterion, Descartes’ rule of signs, Lyapunov function, MATLAB 2012b (ODE 45, DDE 23), MATHEMATICA 11 are the main tools applied for analysis and simulations of mathematical models. We have studied two types of mathematical models: ordinary differential equations (ODEs) model and delay differential equations (DDEs) model. The time delay exists almost in every biological phenomenon and is responsible for the severity of the disease and hence in its treatment. Therefore, the importance of the DDE model cannot be ignored in the control and transmission dynamics of the epidemic. The DDE models have been developed for a better understanding of the transmission dynamics of epidemics.
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Частини книг з теми "NONLINEAR INCIDENCE RATES"

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Dubey, Preeti, Balram Dubey, and Uma S. Dubey. "An SIR Model with Nonlinear Incidence Rate and Holling Type III Treatment Rate." In Applied Analysis in Biological and Physical Sciences, 63–81. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3640-5_4.

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Nilam. "Cause and Control Strategy for Infectious Diseases with Nonlinear Incidence and Treatment Rate." In Studies in Systems, Decision and Control, 61–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49896-2_3.

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3

Zhang, Zizhen, Weishi Zhang, and Anwar Zeb. "Hopf Bifurcation of a Delayed SVEIS Worm Propagation Model with Nonlinear Incidence Rate." In Computational Science and Its Applications – ICCSA 2023 Workshops, 130–43. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37105-9_10.

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4

Liang-liang, Ma, and Tian Fu-peng. "Pneumonia Incidence Rate Predictive Model of Nonlinear Time Series Based on Dynamic Learning Rate BP Neural Network." In Advances in Intelligent and Soft Computing, 739–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14880-4_82.

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Yang, Xiuxiang, Feng Li, and Yuanji Cheng. "Global Stability Analysis on the Dynamics of an SIQ Model with Nonlinear Incidence Rate." In Advances in Intelligent and Soft Computing, 561–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29390-0_89.

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6

Srivastava, Akriti, and Prashant K. Srivastava. "Nonlinear Dynamics in an SIR Model with Ratio-Dependent Incidence and Holling Type III Treatment Rate Functions." In Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics, 57–72. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33050-6_4.

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7

Alla Hamou, Abdelouahed, Elhoussine Azroul, Zakia Hammouch, and Abdelilah Lamrani Alaoui. "Dynamical investigation and simulation of an incommensurate fractional-order model of COVID-19 outbreak with nonlinear saturated incidence rate." In Fractional Order Systems and Applications in Engineering, 245–65. Elsevier, 2023. http://dx.doi.org/10.1016/b978-0-32-390953-2.00022-0.

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Тези доповідей конференцій з теми "NONLINEAR INCIDENCE RATES"

1

Tao Li, Zhi-Hong Guan, Yuanmei Wang, and Yong Li. "Impulsive control of the spread of worms with nonlinear incidence rates." In 2010 Chinese Control and Decision Conference (CCDC). IEEE, 2010. http://dx.doi.org/10.1109/ccdc.2010.5498082.

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2

Tao Li, Zhi-Hong Guan, and Yuanmei Wang. "Impulsive control of epidemic spreading with nonlinear incidence rates on complex networks." In 2012 24th Chinese Control and Decision Conference (CCDC). IEEE, 2012. http://dx.doi.org/10.1109/ccdc.2012.6244480.

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3

Lin, Xiao-Jing, and Ya-Ming Zhuang. "Research on online rumor based on SEIR model with nonlinear incidence rates." In 2015 15th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2015. http://dx.doi.org/10.1109/iccas.2015.7364581.

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4

Chang, Chunling, Yuanwei Jing, and Baoyan Zhu. "Modeling and control for a descriptor epidemic system with nonlinear incidence rates." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407488.

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5

Chang, Chunling, and Yuanwei Jing. "T-S fuzzy modeling and control for a class of epidemic system with nonlinear incidence rates." In 2017 4th International Conference on Information, Cybernetics and Computational Social Systems (ICCSS). IEEE, 2017. http://dx.doi.org/10.1109/iccss.2017.8091403.

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6

Muroya, Yoshiaki, Toshikazu Kuniya, and Yoichi Enatsu. "Global analysis of a multi-group SIR epidemic model with nonlinear incidence rates and distributed moving delays between patches." In The 10'th Colloquium on the Qualitative Theory of Differential Equations. Szeged: Bolyai Institute, SZTE, 2016. http://dx.doi.org/10.14232/ejqtde.2016.8.16.

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7

Lotz, Jeffrey C., Elisa C. Bass, and Diane R. Wagner. "Integration of Mechanical and Biological Criteria When Defining Injury Tolerance." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1920.

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Анотація:
Abstract Degeneration of the intervertebral disc is an important clinical and socio-economic problem. Because of associations between injury rates and physical activity, mechanical factors are thought to play an important role in the incidence and progression of this disease. Bioengineers have historically utilized a strength-of-materials approach to develop tolerance criteria and design interventions meant to reduce injury risk. However, it has become apparent that the disc’s biologic response to loading is an important determinant of degeneration rate. In order to quantify degeneration risk, a hierarchical approach is required which links whole body mechanical exposures to tissue responses that are consistent with the clinical presentation. One challenging aspect of this approach is the definition of accurate constitutive relationships for disc tissues, which are inherently nonlinear, anisotropic and heterogeneous. A second challenge is the development and interpretation of models that allow assessment of the in vivo biologic response to loads. Recent progress in these areas indicates that mechanical and biological factors should be quantitatively linked to provide a comprehensive injury tolerance criteria.
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8

Buonomo, B., and S. Rionero. "Nonlinear Stability of a SIRS Epidemic Model with Convex Incidence Rate." In Proceedings of the International Conference in Honour of Brian Straughan. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789814293228_0003.

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9

Pang, Jianhua, and Jing-an Cui. "An SIRS Epidemiological Model with Nonlinear Incidence Rate Incorporating Media Coverage." In 2009 Second International Conference on Information and Computing Science. IEEE, 2009. http://dx.doi.org/10.1109/icic.2009.235.

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10

Cai, Ruikai, Mingyang Yang, Kangyao Deng, Weilin Zhuge, Bijie Yang, Ricardo Martinez-Botas, and Tao Chen. "Influence of Real Gas Properties on Loss in a Super Critical CO2 (sCO2) Centrifugal Compressor." In ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/gt2022-82151.

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Анотація:
Abstract The performance of the SCO2 centrifugal compressor is the key component influencing the efficiency and stability of the whole Close-Bryton cycle system. It is important to understand the loss mechanism inside the compressor to guide the design and performance optimization of the compressor. However, the physical properties of SCO2 are strongly nonlinear near the critical point, and the internal flow of the compressor is highly coupled with its properties, which inevitably profoundly influences the loss generation in the device. In this paper, the loss mechanism of SCO2 compressor is investigated comprehensively based on numerical method compared with experimental data. CO2 real gas model embodied in RANS model are used for the study. Firstly, grid independence and influence of the resolution of real gas properties tables are discussed. The numerical simulation results are in good agreement with the experimental data of Sandia SCO2 compressor. Secondly, the distribution of the loss of the compressor are evaluated by means of local entropy generation at different mass flow rates. In particular, a direction comparison between the cases with real gas properties and the constant properties is carried out for manifesting of the influence by real gas properties. The results manifest that the loss of the case with constant properties is profoundly higher than that of the real gas properties, especially at small flow rate. Detailed flow field is compared to understand the influence of the properties. It is shown that the tip leakage flow is evidently decreased with the real gas properties and results in a much more uniform flow distribution throughout the impeller. The decrease in static temperature and pressure due to the acceleration of SCO2 at the tip of the main blade causes an increase in fluid density, reducing the tip leakage and secondary flow. Moreover, the influence on the flow in the impeller results in smaller incidence angle near hub side for the case with real gas properties, thus the separation on the suction surface which happens in the case with constant properties is alleviated. Therefore, the loss in both the impeller and diffuser is significantly reduced by the real gas properties.
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