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Comparing Knowledge-Driven and Data-Driven Modeling methods for susceptibility mapping in spatial epidemiology : a case study in Visceral Leishmaniasis

Rajabi, Mohammadreza LU ; Mansourian, Ali LU ; Pilesjö, Petter LU ; Hedefalk, Finn LU ; Groth, Roger LU and Bazmani, Ahad (2014) 17th AGILE International Conference on Geographic Information Science, 2014 In Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6 p.1-5
Abstract
The aim of this study is to compare knowledge-driven and data-driven methods for susceptibility mapping in spatial epidemiology. Our comparison focuses on one of the arguably most important requisites in such models, namely predictability. We compare one data-driven modelling method called Radial Basis Functional Link Net (RBFLN - a well-established Neural Network method) with two knowledge-driven modelling methods, Fuzzy AHP_OWA and Fuzzy GIS-based group decision making (multi criteria decision making methods). These methods are compared in the context of a concrete case study, namely the environmental modelling of Visceral Leishmaniasis (VL) for predictive mapping of risky areas. Our results show that, at least in this particular... (More)
The aim of this study is to compare knowledge-driven and data-driven methods for susceptibility mapping in spatial epidemiology. Our comparison focuses on one of the arguably most important requisites in such models, namely predictability. We compare one data-driven modelling method called Radial Basis Functional Link Net (RBFLN - a well-established Neural Network method) with two knowledge-driven modelling methods, Fuzzy AHP_OWA and Fuzzy GIS-based group decision making (multi criteria decision making methods). These methods are compared in the context of a concrete case study, namely the environmental modelling of Visceral Leishmaniasis (VL) for predictive mapping of risky areas. Our results show that, at least in this particular application, RBFLN model offers the best predictive accuracy (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Visceral Leishmaniasis (VL), spatial epidemiology, prediction, knowledge-driven method, data-driven method.
in
Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6
pages
5 pages
publisher
AGILE, Association of Geographic Information Laboratories for Europe
conference name
17th AGILE International Conference on Geographic Information Science, 2014
language
English
LU publication?
yes
id
3f2adb14-c323-4061-b1ca-5b3638b711a6 (old id 4732672)
alternative location
http://agile-online.org/Conference_Paper/cds/agile_2014/agile2014_126.pdf
date added to LUP
2016-01-14 15:36:19
date last changed
2016-07-04 15:19:18
@inproceedings{3f2adb14-c323-4061-b1ca-5b3638b711a6,
  abstract     = {The aim of this study is to compare knowledge-driven and data-driven methods for susceptibility mapping in spatial epidemiology. Our comparison focuses on one of the arguably most important requisites in such models, namely predictability. We compare one data-driven modelling method called Radial Basis Functional Link Net (RBFLN - a well-established Neural Network method) with two knowledge-driven modelling methods, Fuzzy AHP_OWA and Fuzzy GIS-based group decision making (multi criteria decision making methods). These methods are compared in the context of a concrete case study, namely the environmental modelling of Visceral Leishmaniasis (VL) for predictive mapping of risky areas. Our results show that, at least in this particular application, RBFLN model offers the best predictive accuracy},
  author       = {Rajabi, Mohammadreza and Mansourian, Ali and Pilesjö, Petter and Hedefalk, Finn and Groth, Roger and Bazmani, Ahad},
  booktitle    = {Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6},
  keyword      = {Visceral Leishmaniasis (VL),spatial epidemiology,prediction,knowledge-driven method,data-driven method.},
  language     = {eng},
  pages        = {1--5},
  publisher    = {AGILE, Association of Geographic Information Laboratories for Europe},
  title        = {Comparing Knowledge-Driven and Data-Driven Modeling methods for susceptibility mapping in spatial epidemiology : a case study in Visceral Leishmaniasis},
  year         = {2014},
}