Computational Model Library

Displaying 10 of 1130 results for "Elena A. Pearce" clear search

The Levers of HIV Model

Arthur Hjorth Wouter Vermeer C. Hendricks Brown Uri Wilensky Can Gurkan | Published Tuesday, March 08, 2022 | Last modified Tuesday, October 31, 2023

Chicago’s demographic, neighborhood, sex risk behaviors, sexual network data, and HIV prevention and treatment cascade information from 2015 were integrated as input to a new agent-based model (ABM) called the Levers-of-HIV-Model (LHM). This LHM, written in NetLogo, forms patterns of sexual relations among Men who have Sex with Men (MSM) based on static traits (race/ethnicity, and age) and dynamic states (sexual relations and practices) that are found in Chicago. LHM’s five modules simulate and count new infections at the two marker years of 2023 and 2030 for a wide range of distinct scenarios or levers, in which the levels of PrEP and ART linkage to care, retention, and adherence or viral load are increased over time from the 2015 baseline levels.

Evaluating Government's Policies on Promoting Smart Metering Diffusion in Retail Electricity Markets

Tao Zhang | Published Monday, December 07, 2009 | Last modified Saturday, April 27, 2013

This model is a market game for evaluating the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering in the UK retail electricity market. We break down the policy into four

The ABM looks at how the performance of Water Service Delivery is affected by the relation between management practices and integrity in terms of transparency, accountability and participation

Agent Based Simulation of Technology Adoption

Moeed Haghnevis | Published Tuesday, December 07, 2010 | Last modified Saturday, April 27, 2013

The purpose of this model is to study effect of a particular kind of spatial externality, “fashion effect”, on the dynamics of technology diffusion among rational adopters with uncertainty about the p

This model simulates the form and function of an idealised estuary with associated barrier-spit complex on the north east coast of New Zealand’s North Island (from Bream Bay to central Bay of Plenty) during the years 2010 - 2050 CE. It combines variables from social, ecological and geomorphic systems to simulate potential directions of change in shallow coastal systems in response to external forcing from land use, climate, pollution, population density, demographics, values and beliefs. The estuary is over 1000Ha, making it a large estuary according to Hume et al. (2007) - there are 12 large estuaries in the Auckland region alone (Suyadi et al., 2019). The model was developed as part of Andrew Allison’s PhD Thesis in Geography from the School of Environment and Institute of Marine Science, University of Auckland, New Zealand. The model setup allows for alteration of geomorphic, ecological and social variables to suit the specific conditions found in various estuaries along the north east coast of New Zealand’s North Island.
This model is not a predictive or forecasting model. It is designed to investigate potential directions of change in complex shallow coastal systems. This model must not be used for any purpose other than as a heuristic to facilitate researcher and stakeholder learning and for developing system understanding (as per Allison et al., 2018).

Peer reviewed Horse population dynamics

Nika Galic | Published Tuesday, November 12, 2013 | Last modified Wednesday, October 29, 2014

This model investigates the link between prescribed growth in body size, population dynamics and density dependence through population feedback on available resources.

This is an extension of the basic Suceptible, Infected, Recovered (SIR) model. This model explores the spread of disease in two spaces, one a treatment, and one a control. Through the modeling options, one can explore how changing assumptions about the number of susceptible people, starting number of infected people, the disease’s infection probability, and average duration impacts the outcome. In addition, this version allows users to explore how public health interventions like social distancing, masking, and isolation can affect the number of people infected. The model shows that the interactions of agents, and the interventions can drastically affect the results of the model.

We used the model in our course about COVID-19: https://www.csats.psu.edu/science-of-covid19

ThomondSim

Vinicius Marino Carvalho | Published Monday, April 25, 2022 | Last modified Friday, May 12, 2023

ThomondSim is a simulation of the political and economic landscape of the medieval kingdom of Thomond, southwestern Ireland, between 1276 and 1318.

Its goal is to analyze how deteriorating environmental and economic conditions caused by the Little Ice Age (LIA), the Great European Famine of 1315-1322, and wars between England and Scotland affected the outcomes of a local war involving Gaelic and English aristocratic lineages.
This ABM attempts to model both the effects of devastation on the human environment and the modus operandi of late-medieval war and diplomacy.

The model is the digital counterpart of the science discovery board game The Triumphs of Turlough. Its procedures closely correspond to the game’s mechanics, to the point that ToT can be considered an interactive, analog version of this ABM.

Digital-Twin model of Sejong City

Tae-Sub Yun | Published Wednesday, August 31, 2022

Digital-Twin model of Sejong City – Source model code & data

We only shared model codes, excluding private data and simulation engine codes.
The followings are brief reasons for the items we cannot share.

  1. Residence address data

NOMAD is an agent-based model of firm location choice between two aggregate regions (“near” and “off”) under logistics uncertainty. Firms occupy sites characterised by attractiveness and logistics risk, earn a risk-adjusted payoff that depends on regional costs (wages plus congestion) and an individual risk-tolerance trait, and update location choices using aspiration-based satisficing rules with switching frictions. Logistics risk evolves endogenously on occupied sites through a region-specific absorption mechanism (good/bad events that reduce/increase risk), while congestion feeds back into regional costs via regional shares and local crowding. Runs stop endogenously once the near-region share becomes quasi-stable after burn-in, and the model records time series and quasi-stable outcomes such as near/off composition, switching intensity, costs, average risk, and average risk tolerance.

Displaying 10 of 1130 results for "Elena A. Pearce" clear search

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