Abstract
Many spatial data are prone to uncertainty and imprecision, which calls for a way of representing such information. In this contribution, implementable models for the representation of level-2 fuzzy regions are presented. These models are designed to still adhere to the theoretical model of level-2 fuzzy regions - which employs fuzzy set theory and uses level-2 fuzzy sets to combine imprecision with uncertainty - but impose some limitations and modifications so that they can be represented and used in a computer system. These limitations are mainly aimed at restricting the amount of data that needs to be stored; apart from the representation structures, the operations also need to be defined in an algorithmic and computable way.
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Verstraete, J. (2012). Implementable Representations of Level-2 Fuzzy Regions for Use in Databases and GIS. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_37
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DOI: https://doi.org/10.1007/978-3-642-31709-5_37
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