Preference learning based decision map algebra: specification and implementation

Ahmed Abubahia, Salem Chakhar, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
EditorsZhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
Place of PublicationCham, Switzerland
PublisherSpringer International Publishing
Number of pages12
ISBN (Electronic)978-3-030-29933-0
ISBN (Print)978-3-030-29932-3
Publication statusPublished - Jan 2020
Event19th UK Workshop on Computational Intelligence - Portsmouth, United Kingdom
Duration: 4 Sept 20195 Sept 2019
Conference number: 19

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Workshop19th UK Workshop on Computational Intelligence
Abbreviated titleUKCI 2019
Country/TerritoryUnited Kingdom
OtherThe UKCI 2019 covers both theory and applications in computational intelligence. The topics of interest include
Fuzzy Systems
Neural Networks
Evolutionary Computation
Evolving Systems
Machine Learning
Data Mining
Cognitive Computing
Intelligent Robotics
Hybrid Methods
Deep Learning
Applications of Computational Intelligence
Internet address


  • Decision Map Algebra
  • Preference learning
  • Spatial modelling
  • Multicriteria modelling


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