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A Dynamic Network Model For Population Growth And Urbanization

Year 2019, , 896 - 901, 31.12.2019
https://doi.org/10.17776/csj.632996

Abstract

 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.

References

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  • [8] Bongaarts J., Human population growth and the demographic transition, Philos. T. Roy. Soc. B., 364 (2009) 2985-2990.
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  • [10] Meyer P. S., Ausubel J. H., Carrying capacity: a model with logistically varying limits, Technol. Forecast. Soc., 61 (1999) 209-214.
  • [11] Cohen J. E., Population growth and earth's human carrying capacity, Science, 269 (1995) 341-346.
  • [12] 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.
  • [13] Hopfenberg R., Human carrying capacity is determined by food availability, Popul. Environ., 25 (2003) 109-117.
  • [14] 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.
  • [15] Soffer S. N., Vazquez A., Network clustering coefficient without degree-correlation biases, Phys. Rev. E., 71 (2005) 057101.
  • [16] Benesty J., Chen J., Huang Y., Cohen I., Pearson correlation coefficient. In Noise reduction in speech processing, Springer: Berlin, Heidelberg, 2009.
  • [17] Centola D., The spread of behavior in an online social network experiment, Science, 329 (2010) 1194-1197.
  • [18] 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.
  • [19] Coclite G. M., Garavello M., Piccoli B., Traffic flow on a road network, SIAM J. Math. Anal., 36 (2005) 1862-1886.
  • [20] Serrano M. Á., Boguná M., Percolation and epidemic thresholds in clustered networks, Phys. Rev. Lett., 97 (2006) 088701.
Year 2019, , 896 - 901, 31.12.2019
https://doi.org/10.17776/csj.632996

Abstract

References

  • [1] Goudie A. S., Human impact on the natural environment, 8th ed., Wiley: Hoboken, NJ, USA, 2018.
  • [2] 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.
  • [3] Putterman L., Agriculture, diffusion and development: ripple effects of the neolithic revolution, Economica, 75 (2008) 729-748.
  • [4] Dickinson R. E., City and region: a geographical interpretation, Taylor&Francis: Oxfordshire, UK, 1998.
  • [5] 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.
  • [6] 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.
  • [7] 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.
  • [8] Bongaarts J., Human population growth and the demographic transition, Philos. T. Roy. Soc. B., 364 (2009) 2985-2990.
  • [9] Nowak M. A., Evolutionary dynamics, Harvard University Press: London, UK, 2006.
  • [10] Meyer P. S., Ausubel J. H., Carrying capacity: a model with logistically varying limits, Technol. Forecast. Soc., 61 (1999) 209-214.
  • [11] Cohen J. E., Population growth and earth's human carrying capacity, Science, 269 (1995) 341-346.
  • [12] 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.
  • [13] Hopfenberg R., Human carrying capacity is determined by food availability, Popul. Environ., 25 (2003) 109-117.
  • [14] 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.
  • [15] Soffer S. N., Vazquez A., Network clustering coefficient without degree-correlation biases, Phys. Rev. E., 71 (2005) 057101.
  • [16] Benesty J., Chen J., Huang Y., Cohen I., Pearson correlation coefficient. In Noise reduction in speech processing, Springer: Berlin, Heidelberg, 2009.
  • [17] Centola D., The spread of behavior in an online social network experiment, Science, 329 (2010) 1194-1197.
  • [18] 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.
  • [19] Coclite G. M., Garavello M., Piccoli B., Traffic flow on a road network, SIAM J. Math. Anal., 36 (2005) 1862-1886.
  • [20] Serrano M. Á., Boguná M., Percolation and epidemic thresholds in clustered networks, Phys. Rev. Lett., 97 (2006) 088701.
There are 20 citations in total.

Details

Primary Language English
Journal Section Natural Sciences
Authors

Emir Haliki 0000-0002-5462-6522

Publication Date December 31, 2019
Submission Date October 14, 2019
Acceptance Date December 8, 2019
Published in Issue Year 2019

Cite

APA Haliki, E. (2019). A Dynamic Network Model For Population Growth And Urbanization. Cumhuriyet Science Journal, 40(4), 896-901. https://doi.org/10.17776/csj.632996