Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/72437
Title: Engineering regime shifts in urban systems
Authors: Tan, James Peng Lung
Keywords: DRNTU::Science::General
Issue Date: 2017
Source: Tan, J. P. L. (2017). Engineering regime shifts in urban systems. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Measures of wealth and production have been found to scale superlinearly with the population of a city. Therefore, it makes economic sense for humans to congregate together in dense settlements. A recent model of population dynamics showed that population growth can become superexponential due to the superlinear scaling of production with population in a city. In Chapter \ref{chapter:Introduction}, we generalize this population dynamics model and demonstrate the existence of multiple stable equilibrium points, showing how population growth can be stymied by a poor economic environment. This occurs when the goods and services produced by the city become less profitable due to a lack of diversification in the city's economy. Then, we propose to utilize critical slowing down signals related to the stability of an equilibrium point to engineer regime shifts in the city so that the city may continue to grow again. In Chapters \ref{chapter:USHousing} and \ref{chapter:SocialSensing}, we demonstrate the existence of critical slowing down signals associated with regime shifts in two real-world complex systems: the US housing market and the online Singaporean sociopolitical landscape respectively. In Chapter \ref{chapter:Stability}, we furnish a sufficient condition for instability for an equilibrium point. This is useful for the engineering of regime shifts if a bifurcation parameter cannot be identified readily. Next, we present a pseudocode of the algorithm in Chapter \ref{chapter:Algorithm}. Finally, in Chapter \ref{chapter:Discussion}, we conclude and discuss possible directions for future work. The generality of the model and the algorithm used here implies that the model and algorithm need not be restricted to urban systems; they are easily applicable to other types of systems where the assumptions used are valid. The results presented in Chapter \ref{chapter:USHousing} have been published in the \textit{European Journal of Physical Sciences B} (2014) and \textit{PLoS ONE} (2016) \cite{JPLTanEPJB, TanPLOSONE1}. The results presented in Chapter \ref{chapter:SocialSensing} have been submitted to a journal. The results presented in Chapter \ref{chapter:Stability} have been published in \textit{Scientific Reports} \cite{TanSciRep1}. The results presented in Chapters \ref{chapter:Introduction} and \ref{chapter:Algorithm} are currently under review at a journal. This thesis contains text, figures, and tables lifted verbatim from the aforementioned publications and those manuscripts pending to be published.
URI: http://hdl.handle.net/10356/72437
DOI: 10.32657/10356/72437
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:IGS Theses

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