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Comparing Knowledge...
Comparing Knowledge-Driven and Data-Driven Modeling methods for susceptibility mapping in spatial epidemiology : a case study in Visceral Leishmaniasis
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- Rajabi, Mohammadreza (författare)
- Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
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- Mansourian, Ali (författare)
- Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
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- Pilesjö, Petter (författare)
- Lund University,Lunds universitet,Centrum för geografiska informationssystem (GIS-centrum),Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Centrum för Mellanösternstudier (CMES),Samhällsvetenskapliga institutioner och centrumbildningar,Samhällsvetenskapliga fakulteten,Centre for Geographical Information Systems (GIS Centre),Dept of Physical Geography and Ecosystem Science,Faculty of Science,Centre for Advanced Middle Eastern Studies (CMES),Departments of Administrative, Economic and Social Sciences,Faculty of Social Sciences
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- Hedefalk, Finn (författare)
- Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
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- Groth, Roger (författare)
- Lund University,Lunds universitet,Centrum för geografiska informationssystem (GIS-centrum),Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Centre for Geographical Information Systems (GIS Centre),Dept of Physical Geography and Ecosystem Science,Faculty of Science
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- Bazmani, Ahad (författare)
- Tabriz University of Medical Sciences
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(creator_code:org_t)
- 2014
- 2014
- Engelska 5 s.
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Ingår i: Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6. ; , s. 1-5
- Relaterad länk:
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http://agile-online.... (free)
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https://lup.lub.lu.s...
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Abstract
Ämnesord
Stäng
- 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
Ämnesord
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)
Nyckelord
- Visceral Leishmaniasis (VL)
- spatial epidemiology
- prediction
- knowledge-driven method
- data-driven method.
- Artificial Intelligence (AI)
- Geospatial Artificial Intelligence (GeoAI)
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)