New Combining Rules for Spatial Clustering Methods Using Sigma-Count for Spatial Epidemiology

Autor: Jordana de Almeida Nogueira, Liliane dos Santos Machado, Laísa Ribeiro de Sá, Ronei Marcos de Moraes
Rok vydání: 2020
Předmět:
Zdroj: 2020 International Conference on Decision Aid Sciences and Application (DASA).
DOI: 10.1109/dasa51403.2020.9317161
Popis: In Epidemiology, the study of several diseases is related to the geographical territory in which it occurs. Some spatial clustering methods are able to perform statistical decision about the significance of territories. However, each method is based on a different methodology, providing different results as well. Recently, some authors proposed combining spatial clustering methods in order to provide more accurate results. This paper propose two new combining rules based on Cardinality of Fuzzy Sets, generalizing the classical Majority Voting and Plurality Voting. A study of case using real Dengue Fever epidemiological data and combining five spatial clustering methods was performed. In this study the Fuzzy Plurality Voting provided better decision map than the classical ones, when compared to a reference map.
Databáze: OpenAIRE