Nüfus Artışı ve Kentleşme İçin Dinamik Bir Ağ Modeli

Dinamik ağlar, zaman içinde değişiklik gösteren durumları belirtmekte ve bu değişiklikler genellikle bir ağın topolojisi ile ilişkilendirilmektedir. Ağ modeli olarak tanımlanabilecek birçok sistem için dinamik modellere ihtiyaç duyulmaktadır. Canlı organizmaların yayılması ile ilgili olanlar da bu duruma bir örnektir. Çalışmada insan nüfusunun ağ topolojisi tanımlanarak ile bir örnek uzay oluşturulmuş, nüfus artışı ile içerisinde nasıl bir yayılma görüleceği araştırılmış ve nüfus büyümesinin modellenen dinamik ağdaki çeşitli değişkenler ile aralarındaki korelasyonlar incelenmiştir.

A Dynamic Network Model For Population Growth And Urbanization

Dynamic networks imply those states of which change over time and such changes are generally associated with the topology of a network. Dynamic models are currently needed for numerous systems which could be defined as a network model. Those related to the propagation of living organisms are also a typical example. The study has examined a sample space which has been defined in the network topology of human population as the way in which it will spread with population growth and correlated with various variables in the modeled dynamic network.

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Goudie A. S., Human impact on the natural environment, 8th ed., Wiley: Hoboken, NJ, USA, 2018.
Kuijt I. J., People and space in early agricultural villages: exploring daily lives, community size, and architecture in the Late Pre-Pottery Neolithic, Anthropol. Archaeol., 19 (2000) 75-102.
Putterman L., Agriculture, diffusion and development: ripple effects of the neolithic revolution, Economica, 75 (2008) 729-748.
Dickinson R. E., City and region: a geographical interpretation, Taylor&Francis: Oxfordshire, UK, 1998.
Clark J. S., Lewis M., McLachlan J. S., HilleRisLambers J., Estimating population spread: what can we forecast and how well?, Ecology, 84 (2003) 1979-1988.
Haydon D. T., Morales J. M., Yott A., Jenkins D. A., Rosatte R., Fryxell J. M. P., Socially informed random walks: incorporating group dynamics into models of population spread and growth, Roy. Soc. B. Biol. Sci., 275 (2008) 1101-1109.
Wittemyer G., Elsen P., Bean W. T., Burton A. C. O., Brashares J. S., Accelerated human population growth at protected area edges, Science, 321 (2008) 123-126.
Bongaarts J., Human population growth and the demographic transition, Philos. T. Roy. Soc. B., 364 (2009) 2985-2990.
Nowak M. A., Evolutionary dynamics, Harvard University Press: London, UK, 2006.
Meyer P. S., Ausubel J. H., Carrying capacity: a model with logistically varying limits, Technol. Forecast. Soc., 61 (1999) 209-214.
Cohen J. E., Population growth and earth's human carrying capacity, Science, 269 (1995) 341-346.
Graymore M. L., Sipe N. G., Rickson R. E., Sustaining human carrying capacity: a tool for regional sustainability assessment, Ecol. Econ., 69 (2010) 459-468.
Hopfenberg R., Human carrying capacity is determined by food availability, Popul. Environ., 25 (2003) 109-117.
Yang X., Megson G. M., Tang Y. Y., Xing Y., Largest connected component of a star graph with faulty vertices, Int. J. Comput. Math., 85 (2008) 1771-1778.
Soffer S. N., Vazquez A., Network clustering coefficient without degree-correlation biases, Phys. Rev. E., 71 (2005) 057101.
Benesty J., Chen J., Huang Y., Cohen I., Pearson correlation coefficient. In Noise reduction in speech processing, Springer: Berlin, Heidelberg, 2009.
Centola D., The spread of behavior in an online social network experiment, Science, 329 (2010) 1194-1197.
Jeger M. J., Pautasso M., Holdenrieder O., Shaw M. W., Modelling disease spread and control in networks: implications for plant sciences, New Phytol., 174 (2007) 279-297.
Coclite G. M., Garavello M., Piccoli B., Traffic flow on a road network, SIAM J. Math. Anal., 36 (2005) 1862-1886.
Serrano M. Á., Boguná M., Percolation and epidemic thresholds in clustered networks, Phys. Rev. Lett., 97 (2006) 088701.