Modeling population dynamics in the city: from a regional to a multi-agent approach.
Benenson, Itzhak (1999)
Discrete Dynamics in Nature and Society
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Displaying similar documents to “Population growth and environment as a self-organizing system.”
Modeling population dynamics in the city: from a regional to a multi-agent approach.
Medical cost trajectories and onsets of cancer and noncancer diseases in US elderly population.
Akushevich, Igor, Kravchenko, Julia, Akushevich, Lucy, Ukraintseva, Svetlana, Arbeev, Konstantin, Yashin, Anatoliy I. (2011)
Computational & Mathematical Methods in Medicine
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Stimulus, expectations, desires and response strategies: The building blocks of nonlinear interaction dynamics.
Dendrinos, Dimitrios S. (2002)
Discrete Dynamics in Nature and Society
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Growth, technology, and environmental change -- nonlinearity and non-constant returns.
Zhang, Wei-Bin (2002)
Discrete Dynamics in Nature and Society
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Physics and the foundations of economic science: comments in memory of Ilya Prigogine.
Day, Richard H. (2004)
Discrete Dynamics in Nature and Society
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Sociodynamics applied to the evolution of urban and regional structures.
Weidlich, Wolfgang (1997)
Discrete Dynamics in Nature and Society
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A simple nonlinear dynamic model for unemployment: Explaining the spanish case.
Faria, João Ricardo, León-Ledesma, Miguel A. (2008)
Discrete Dynamics in Nature and Society
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Rumor propagation model: an equilibrium study.
Piqueira, José Roberto C. (2010)
Mathematical Problems in Engineering
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Multiagent opinion dynamics influenced by individual susceptibility and anchoring effect
Zihan Chen, Yu Xing, Huashu Qin (2019)
Kybernetika
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This paper studies a new model of social opinion dynamics in multiagent system by counting in two important factors, individual susceptibility and anchoring effect. Different from many existing models only focusing on one factor, this model can exhibit not only agreement phenomena, but also disagreement phenomena such as clustering and fluctuation, during opinion evolution. Then we provide several conditions to show how individual susceptibility and anchoring effect work on steady-state...
Prevalence of aquatic insects and arsenic concentration determine the geographical distribution of mycobacterium ulcerans infection.
Aidoo, Anthony Y., Osei, Bonsu (2007)
Computational & Mathematical Methods in Medicine
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