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Comparisons between different multi-criteria decision analysis techniques for disease susceptibility mapping

Dong, Shuzhi LU (2016) In Student thesis series INES NGEM01 20161
Dept of Physical Geography and Ecosystem Science
Abstract
Geographic information system multi-criteria decision analysis (GIS-MCDA) procedure can combine criterion maps together and associated the criterion weights to acquire an overall value for each spatial location in the research area. Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Ordered Weighted averaging (OWA) are three generic algorithms of multi-criteria decision analysis. These have been combined with GIS to tackle wide range of spatial problems.

In this research, the comparison of AHP, TOPSIS, and OWA methods for susceptibility mapping in spatial communicable disease study had been made through testing the sensitivity of each model. The methods are compered by two... (More)
Geographic information system multi-criteria decision analysis (GIS-MCDA) procedure can combine criterion maps together and associated the criterion weights to acquire an overall value for each spatial location in the research area. Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Ordered Weighted averaging (OWA) are three generic algorithms of multi-criteria decision analysis. These have been combined with GIS to tackle wide range of spatial problems.

In this research, the comparison of AHP, TOPSIS, and OWA methods for susceptibility mapping in spatial communicable disease study had been made through testing the sensitivity of each model. The methods are compered by two concrete case studies: modelling of visceral leishmaniasis in north-western Iran for mapping of risky areas and modelling of dengue disease in Ecuador for mapping of risky areas. In regard to testing the algorithms, prediction-rate method was utilized to draw the receiver operating characteristic (ROC) curve. Comparing the tendency of ROC curves and the risk-prone areas of the disease from susceptibility maps, also considering the realistic situations of two infectious diseases, evaluations of these three algorithms had been done.

In this research, at least in this application, AHP model offers the best predictive accuracy in both of these two case studies. (Less)
Popular Abstract
Geographic information system multi-criteria decision analysis (GIS-MCDA) technique can combine multiple criterion maps together and associated the criterion weights to acquire an overall value for each spatial location in the research area. Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Ordered Weighted averaging (OWA) are three generic algorithms of multi-criteria decision analysis. These three methods can be used in GIS analysis to solve some spatial problems,

In this research, the implementation of these three methods for susceptibility mapping in spatial communicable disease will be done. The two case studies used for the models were: visceral leishmaniasis disease... (More)
Geographic information system multi-criteria decision analysis (GIS-MCDA) technique can combine multiple criterion maps together and associated the criterion weights to acquire an overall value for each spatial location in the research area. Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Ordered Weighted averaging (OWA) are three generic algorithms of multi-criteria decision analysis. These three methods can be used in GIS analysis to solve some spatial problems,

In this research, the implementation of these three methods for susceptibility mapping in spatial communicable disease will be done. The two case studies used for the models were: visceral leishmaniasis disease in north-western Iran, dengue disease in Ecuador. In regard to testing these three models to find the suitable one for disease prediction, prediction-rate method was utilized for evaluations. For the results, at least in this application, AHP model offers the best predictive accuracy in both of these two case studies. (Less)
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author
Dong, Shuzhi LU
supervisor
organization
course
NGEM01 20161
year
type
H2 - Master's Degree (Two Years)
subject
keywords
TOPSIS, multi-criteria decision analysis, AHP, OWA, disease susceptibility mapping, physical geography and ecosystem analysis, geomatics
publication/series
Student thesis series INES
report number
392
language
English
id
8884943
date added to LUP
2016-06-27 09:14:04
date last changed
2016-06-27 09:14:04
@misc{8884943,
  abstract     = {Geographic information system multi-criteria decision analysis (GIS-MCDA) procedure can combine criterion maps together and associated the criterion weights to acquire an overall value for each spatial location in the research area. Analytical Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Ordered Weighted averaging (OWA) are three generic algorithms of multi-criteria decision analysis. These have been combined with GIS to tackle wide range of spatial problems. 

In this research, the comparison of AHP, TOPSIS, and OWA methods for susceptibility mapping in spatial communicable disease study had been made through testing the sensitivity of each model. The methods are compered by two concrete case studies: modelling of visceral leishmaniasis in north-western Iran for mapping of risky areas and modelling of dengue disease in Ecuador for mapping of risky areas. In regard to testing the algorithms, prediction-rate method was utilized to draw the receiver operating characteristic (ROC) curve. Comparing the tendency of ROC curves and the risk-prone areas of the disease from susceptibility maps, also considering the realistic situations of two infectious diseases, evaluations of these three algorithms had been done.

In this research, at least in this application, AHP model offers the best predictive accuracy in both of these two case studies.},
  author       = {Dong, Shuzhi},
  keyword      = {TOPSIS,multi-criteria decision analysis,AHP,OWA,disease susceptibility mapping,physical geography and ecosystem analysis,geomatics},
  language     = {eng},
  note         = {Student Paper},
  series       = {Student thesis series INES},
  title        = {Comparisons between different multi-criteria decision analysis techniques for disease susceptibility mapping},
  year         = {2016},
}