A Genetic Algorithm Approach to Exploring Simulation Parameters

dc.contributor.authorAhmad, Saira
dc.date.accessioned2012-09-14T14:22:24Z
dc.date.available2012-09-14T14:22:24Z
dc.date.copyright2012-09
dc.date.created2012-08-16
dc.date.issued2012-09-14
dc.degree.departmentDepartment of Computing and Information Scienceen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameMaster of Scienceen_US
dc.degree.programmeComputer Scienceen_US
dc.description.abstractSimulation of animal disease spread is essential for understanding and controlling the outbreak of disease among herds of livestock (in particular cattle and poultry). Using a computerized system or simulator, animal health professionals or epidemiologists often spend many hours determining the set of input parameters that most accurately represent a disease spread or an outbreak scenario. A parameter can be a simple boolean value, or a scientific or often hypothetically derived range of real numbers. Many times, an epidemiologist chooses a value provisionally in a random fashion and repeats the simulation until a viable solution is achieved. This tedious process is inefficient and lengthy. To assist and improve this laborious practice in a concise and timely manner, a Genetic Algorithm is employed to determine a population based solution consisting of input parameters using the North American Animal Disease Spread Model (NAADSM).en_US
dc.identifier.urihttp://hdl.handle.net/10214/3996
dc.language.isoenen_US
dc.publisherUniversity of Guelphen_US
dc.rightsAttribution 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/ca/*
dc.subjectGenetic Algorithmen_US
dc.subjectanimal disease spread simulatoren_US
dc.subjectstochastic simulationen_US
dc.subjectsimulationen_US
dc.subjectsimulation parametersen_US
dc.titleA Genetic Algorithm Approach to Exploring Simulation Parametersen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Ahmad_Saira_201209_Msc.pdf
Size:
2.92 MB
Format:
Adobe Portable Document Format
Description:
Master of Science Thesis
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
317 B
Format:
Item-specific license agreed upon to submission
Description: