@inproceedings{5317996bc897483585ba957799e54cf7,
title = "Preference Learning Based Decision Map Algebra: Specification and Implementation",
abstract = "Decision Map Algebra (DMA) is a generic and context independent algebra, especially devoted to spatial multicriteria modelling. The algebra defines a set of operations which formalises spatial multicriteria modelling and analysis. The main concept in DMA is decision map, which is a planar subdivision of the study area represented as a set of non-overlapping polygonal spatial units that are assigned, using a multicriteria classification model, into an ordered set of classes. Different methods can be used in the multicriteria classification step. In this paper, the multicriteria classification step relies on the Dominance-based Rough Set Approach (DRSA), which is a preference learning method that extends the classical rough set theory to multicriteria classification. The paper first introduces a preference learning based approach to decision map construction. Then it proposes a formal specification of DMA. Finally, it briefly presents an object oriented implementation of DMA.",
author = "AHMED ABUBAHIA and Salem Chakhar and Mihaela Cocea",
year = "2019",
month = aug,
day = "30",
language = "English",
isbn = "978-3-030-29932-3",
series = "Advances in Intelligent Systems and Computing ",
publisher = "Springer Cham",
pages = "342--353",
booktitle = "Advances in Computational Intelligence Systems",
}