Computational Model Library

Displaying 10 of 112 results for "Yunnan University" clear search

This simulation model is to simulate the emergence of technological innovation processes from the hypercycles perspective.

The model presented here was created as part of my dissertation. It aims to study the impacts of topography and climate change on prehistoric networks, with a focus on the Magdalenian, which is dated to between 20 and 14,000 years ago.

The Land Use Competition in Drylands (LUCID) model is a stylized agent-based model of a smallholder farming system. Its main purpose is to illustrate how competition between pastoralism and crop cultivation can affect livelihoods of households, specifically their food security. In particular, the model analyzes whether the expansion of crop cultivation may contribute to a vicious circle where an increase in cultivated area leads to higher grazing pressure on the remaining pastureland, which in turn may cause forage shortages and livestock loss for households which are then forced to further expand their cultivated area in order to increase their food security. The model does not attempt to replicate a particular case study but to generate a general understanding of mechanisms and drivers of such vicious circles and to identify possible scenarios under which such circles may be prevented.

The model is inspired by observations of the Borana land use system in Southern Ethiopia. The climatic and ecological conditions of the Borana zone favor pastoralism, and traditionally livelihoods have been based mainly on livestock keeping. Recent years, however, have seen an advancement of crop cultivation as a coping strategy, e.g., to compensate the loss of livestock, even though crop yields are low on average and successful harvests are infrequent.

In the model, it is possible to evaluate patterns of individual (single household) as well as overall (across all households) consumption and food security, depending on a range of ecological, climatic and management parameters.

Retail Competition Agent-based Model

Jiaxin Zhang Derek Robinson | Published Sunday, January 03, 2021 | Last modified Wednesday, November 10, 2021

The Retail Competition Agent-based Model (RC-ABM) is designed to simulate the retail competition system in the Region of Waterloo, Ontario, Canada, which which explicitly represents store competition behaviour. Through the RC-ABM, we aim to answer 4 research questions: 1) What is the level of correspondence between market share and revenue acquisition for an agent-based approach compared to a traditional location-allocation-based approach? 2) To what degree can the observed store spatial pattern be reproduced by competition? 3) To what degree are their path dependent patterns of retail success? 4) What is the relationship between retail survival and the endogenous geographic characteristics of stores and consumer expenditures?

This model was built to estimate the impacts of exogenous fodder input and credit loans services on livelihood, rangeland health and profits of pastoral production in a small holder pastoral household in the arid steppe rangeland of Inner Mongolia, China. The model simulated the long-term dynamic of herd size and structure, the forage demand and supply, the cash flow, and the situation of loan debt under three different stocking strategies: (1) No external fodder input, (2) fodders were only imported when natural disaster occurred, and (3) frequent import of external fodder, with different amount of available credit loans. Monte-Carlo method was used to address the influence of climate variability.

This model uses ’satisficing’ as a model for farmers’ decision making to learn about influences of alternative decision-making models on simulation results and to exemplify a way to transform a rather theoretical concept into a feasible decision-making model for agent-based farming models.

Peer reviewed Simulating the Economic Impact of Boko Haram on a Cameroonian Floodplain

Nathaniel Henry Sarah Laborde Mark Moritz | Published Saturday, October 22, 2016 | Last modified Wednesday, June 07, 2017

This model examines the potential impact of market collapse on the economy and demography of fishing households in the Logone Floodplain, Cameroon.

Zombies

Jennifer Badham | Published Tuesday, June 08, 2021

Zombies move toward humans and humans move (faster) away from zombies. They fight if they meet, and humans who lose become zombies.

Social model of a Team Developing a Planning-Methodology

Oswaldo Terán Christophe Sibertin | Published Monday, November 18, 2013 | Last modified Sunday, November 16, 2014

The model represents a team intended at designing a methodology for Institutional Planning. Included in ICAART’14 to exemplify how emotions can be identified in SocLab; and in ESSA’14 to show the Efficiency of Organizational Withdrawal vs Commitment.

Peer reviewed Visibility of archaeological social networks

Claudine Gravel-Miguel | Published Sunday, November 26, 2023

The purpose of this model is to explore the impact of combining archaeological palimpsests with different methods of cultural transmission on the visibility of prehistoric social networks. Up until recently, Paleolithic archaeologists have relied on stylistic similarities of artifacts to reconstruct social networks. However, this method - which is successfully applied to more recent ceramic assemblages - may not be applicable to Paleolithic assemblages, as several of those consist of palimpsests of occupations. Therefore, this model was created to study how palimpsests of occupation affect our social network reconstructions.

The model simplifies inter-groups interactions between populations who share cultural traits as they produce artifacts. It creates a proxy archaeological record of artifacts with stylistic traits that can then be used to reconstruct interactions. One can thus use this model to compare the networks reconstructed through stylistic similarities with direct contact.

Displaying 10 of 112 results for "Yunnan University" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept