Computational Model Library

Displaying 10 of 359 results for "John C Moore" clear search

Residents planned behaviour of waste sorting to explore urban situations

Jonathan Edgardo Cohen | Published Wednesday, June 07, 2023 | Last modified Thursday, March 14, 2024

Municipal waste management (MWM) is essential for urban development. Efficient waste management is essential for providing a healthy and clean environment, for reducing GHGs and for increasing the amount of material recycled. Waste separation at source is perceived as an effective MWM strategy that relays on the behaviour of citizens to separate their waste in different fractions. The strategy is straightforward, and many cities have adopted the strategy or are working to implement it. However, the success of such strategy depends on adequate understanding of the drivers of the behaviour of proper waste sorting. The Theory of Planned Behaviour (TPB) has been extensively applied to explain the behaviour of waste sorting and contributes to determining the importance of different psychological constructs. Although, evidence shows its validity in different contexts, without exploring how urban policies and the built environment affect the TPB, its application to urban challenges remains unlocked. To date, limited research has focused in exposing how different urban situations such as: distance to waste bins, conditions of recycling facilities or information campaigns affect the planned behaviour of waste separation. To fill this gap, an agent-based model (ABM) of residents capable of planning the behaviour of waste separation is developed. The study is a proof of concept that shows how the TPB can be combined with simulations to provide useful insights to evaluate different urban planning situations. In this paper we depart from a survey to capture TPB constructs, then Structural Equation Modelling (SEM) is used to validate the TPB hypothesis and extract the drivers of the behaviour of waste sorting. Finally, the development of the ABM is detailed and the drivers of the TPB are used to determine how the residents behave. A low-density and a high-density urban scenario are used to extract policy insights. In conclusion, the integration between the TPB into ABMs can help to bridge the knowledge gap between can provide a useful insight to analysing and evaluating waste management scenarios in urban areas. By better understanding individual waste sorting behaviour, we can develop more effective policies and interventions to promote sustainable waste management practices.

Peer reviewed AMRO_CULEX_WNV

Aniruddha Belsare Jennifer Owen | Published Saturday, February 27, 2021 | Last modified Thursday, March 11, 2021

An agent-based model simulating West Nile Virus dynamics in a one host (American robin)-one vector (Culex spp. mosquito) system. ODD improved and code cleaned.

A generalized organizational agent- based model (ABM) containing both formal organizational hierarchy and informal social networks simulates organizational processes that occur over both formal network ties and informal networks.

This model is based on the Narragansett Bay, RI recreational fishery. The two types of agents are piscivorous fish and fishers (shore and boat fishers are separate “breeds”). Each time step represents one week. Open season is weeks 1-26, assuming fishing occurs during half the year. At each weekly time step, fish agents grow, reproduce, and die. Fisher agents decide whether or not to fish based on their current satisfaction level, and those that do go fishing attempt to catch a fish. If they are successful, they decide whether to keep or release the fish. In our publication, this model was linked to an Ecopath with Ecosim food web model where the commercial harvest of forage fish affected the biomass of piscivorous fish - which then became the starting number of piscivorous fish for this ABM. The number of fish caught in a season of this ABM was converted to a fishing pressure and input back into the food web model.

This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.

NarrABS

Tilman Schenk | Published Thursday, September 20, 2012 | Last modified Saturday, April 27, 2013

An agent based simulation of a political process based on stakeholder narratives

Universal Darwinism in Dutch Greenhouses

Julia Kasmire | Published Wednesday, May 09, 2012 | Last modified Saturday, April 27, 2013

An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.

CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

a computer-based role-playing game simulating the interactions between farming activities, livestock herding and wildlife in a virtual landscape reproducing local socioecological dynamics at the periphery of Hwange National Park (Zimbabwe).

HUMLAND Fire-in-the-Hole is a conceptual agent-based model (ABM) designed to explore the ecological and behavioral consequences of fire-driven hunting strategies employed by hunter-gatherers, specifically Neanderthals, during the Last Interglacial period around the Neumark-Nord (Germany) archaeological site.

This model builds on and specializes the HUMLAND 1.0.0 model (Nikulina et al. 2024), integrating anthropogenic fires, elephant group behavior, and landscape response to simulate interactions between humans, megafauna, and vegetation over time.

Displaying 10 of 359 results for "John C Moore" 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