Agent-based modeling of urban complexity
In this article, Dr. Monterola and Dr. Legara explain why cities like Singapore should be understood as complex systems, and how we can better understand cities through agent-based models. – Assoc. Prof. Cheong Siew Ann
Assessing the Feasibility of Relief Operations
Given the level of risk that we, as a country, are exposed to (e.g. from earthquakes and typhoons), it is easy to see that there is a compelling need for our government to set up effective disaster preparedness and relief response plans, especially considering the fact that we can never be immune to natural disasters.
Machine Learning and the Smart City
On 19 February 2016, I participated as speaker at the Humans+Machines conference organized by the Thinking Machines. Below is a copy of the slide deck I used.
How Voters Combine Candidates on the Ballot: The Case of the Philippine Senatorial Elections
In the Philippines, senators are nationally elected officials, and citizens vote for 12 candidates every three years. The country’s electoral features include a weak party system, a low-information environment for … Continue reading
News Frames of the Population Issue in the Philippines
Using automated semantic network analysis, this study examines media framing of the population issue in the Philippines through the different labels used to refer to it in public discourse. The … Continue reading
Mechanism-based model of a mass rapid transit system: A perspective
In this paper, we discuss our findings on the spatiotemporal dynamics within the mass rapid transit (MRT) system of Singapore. We show that the trip distribution of Origin-Destination (OD) station … Continue reading
Simulating Congestion Dynamics of Train Rapid Transit
Investigating congestion in train rapid transit systems (RTS) in today’s urban cities is a challenge compounded by limited data availability and difficulties in model validation. Here, we integrate information from … Continue reading
