Computational Model Library

Displaying 10 of 315 results for 'Tim Dorscheidt'

Neolithic Spread Model Version 1.0

Sean Bergin Michael Barton Salvador Pardo Gordo Joan Bernabeu Auban | Published Thursday, December 11, 2014 | Last modified Monday, December 31, 2018

This model simulates different spread hypotheses proposed for the introduction of agriculture on the Iberian peninsula. We include three dispersal types: neighborhood, leapfrog, and ideal despotic distribution (IDD).

UK Demographic Simulator

Tony Lawson | Published Monday, February 27, 2012 | Last modified Tuesday, October 21, 2014

A dynmaic microsimulation model to project the UK population over time

Ornstein-Uhlenbeck Pandemic package

Peter Cotton | Published Friday, April 24, 2020 | Last modified Friday, May 08, 2020

Pandemic (pip install pandemic)

An agent model in which commuting, compliance, testing and contagion parameters drive infection in a population of thousands of millions. Agents follow Ornstein-Uhlenbeck processes in the plane and collisions drive transmission. Results are stored at SwarmPrediction.com for further analysis, and can be retrieved by anyone.

This is a very simple simulation that in a special case can be shown to be approximated by a compartmental model with time varying infection rate.

AgriAdopt

Sebastian Rasch | Published Tuesday, March 26, 2024

The purpose of this model is to project the dynamics of technology adoption of autonomous weeding robots by sugar beet producing farmers in North Rhine-Westphalia (NRW). Moreover, the design of the model serves the purpose to investigate second-order effects of robot adoption on shifts in farm income and on production quantities of main crops produced in North Rhine-Westphalia. One aim is to analyse the impact of technology attributes and costs of pesticides on adoption patterns.

This is a simulation model of communication between two groups of managers in the course of project implementation. The “world” of the model is a space of interaction between project participants, each of which belongs either to a group of work performers or to a group of customers. Information about the progress of the project is publicly available and represents the deviation Earned value (EV) from the planned project value (cost baseline).
The key elements of the model are 1) persons belonging to a group of customers or performers, 2) agents that are communication acts. The life cycle of persons is equal to the time of the simulation experiment, the life cycle of the communication act is 3 periods of model time (for the convenience of visualizing behavior during the experiment). The communication act occurs at a specific point in the model space, the coordinates of which are realized as random variables. During the experiment, persons randomly move in the model space. The communication act involves persons belonging to a group of customers and a group of performers, remote from the place of the communication act at a distance not exceeding the value of the communication radius (MaxCommRadius), while at least one representative from each of the groups must participate in the communication act. If none are found, the communication act is not carried out. The number of potential communication acts per unit of model time is a parameter of the model (CommPerTick).

The managerial sense of the feedback is the stimulating effect of the positive value of the accumulated communication complexity (positive background of the project implementation) on the productivity of the performers. Provided there is favorable communication (“trust”, “mutual understanding”) between the customer and the contractor, it is more likely that project operations will be performed with less lag behind the plan or ahead of it.
The behavior of agents in the world of the model (change of coordinates, visualization of agents’ belonging to a specific communicative act at a given time, etc.) is not informative. Content data are obtained in the form of time series of accumulated communicative complexity, the deviation of the earned value from the planned value, average indicators characterizing communication - the total number of communicative acts and the average number of their participants, etc. These data are displayed on graphs during the simulation experiment.
The control elements of the model allow seven independent values to be varied, which, even with a minimum number of varied values (three: minimum, maximum, optimum), gives 3^7 = 2187 different variants of initial conditions. In this case, the statistical processing of the results requires repeated calculation of the model indicators for each grid node. Thus, the set of varied parameters and the range of their variation is determined by the logic of a particular study and represents a significant narrowing of the full set of initial conditions for which the model allows simulation experiments.

The Travel-tour case study

Christophe Sibertin-Blanc Françoise Adreit Joseph El Gemayel | Published Sunday, May 19, 2013 | Last modified Friday, June 14, 2013

This model describes and analyses the Travel-Tour Case study.

Peer reviewed Pumpa irrigation model

Irene Perez Ibarra Marco Janssen | Published Wednesday, January 09, 2013 | Last modified Saturday, April 27, 2013

This is a replication of the Pumpa model that simulates the Pumpa Irrigation System in Nepal (Cifdaloz et al., 2010).

This software simulates cars and bicycles as traffic participants while crossing different crossroad designs such as roundabouts, protected crossroads and standard crossroads. It is written in Netlogo 6.2 and aims to identify safety characteristics of these layouts using agent-based modeling. Participants track the line of sight to each other and print them as an output alongside with the adjacent destination, used layout, count of collisions/cars/bicycles and time.

Detailed information can be found within the info tab of the program itself.

Interactions between organizations and social networks in common-pool resource governance

Phesi Project | Published Monday, October 29, 2012 | Last modified Saturday, April 27, 2013

Explores how social networks affect implementation of institutional rules in a common pool resource.

The simulation model conducts fine-grained population projection by specifying life course dynamics of individuals and couples by means of traditional demographic microsimulation and by using agent-based modeling for mate matching.

Displaying 10 of 315 results for 'Tim Dorscheidt'

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