Spatial rough set-based geographical detectors for nominal target variables

H Bai, D Li, Y Ge, J Wang, F Cao - Information Sciences, 2022 - Elsevier
Spatial rough set theory is an extension of classical rough set theory that is designed to
handle spatial data. Different from its classical analog, spatial rough set theory approximates …

A fuzzy rough sets-based data-driven approach for quantifying local and overall fuzzy relations between variables for spatial data

H Bai, J Jing, D Li, Y Ge - Applied Soft Computing, 2024 - Elsevier
Exploring the relationships between variables is a crucial component in comprehending
geographical phenomena. Most existing methods ignore the vagueness hidden in spatial …

[PDF][PDF] The use of rough rules in the selection of topographic objects for generalizing geographical information

A Fiedukowicz - Polish Cartographical Review, 2020 - sciendo.com
Selection is a key element of the cartographic generalisation process, often being its first
stage. On the other hand it is a component of other generalisation operators, such as …

A spatial heterogeneity-based rough set extension for spatial data

H Bai, D Li, Y Ge, J Wang - International Journal of Geographical …, 2019 - Taylor & Francis
When classical rough set (CRS) theory is used to analyze spatial data, there is an
underlying assumption that objects in the universe are completely randomly distributed over …

Metodyka wykorzystania reduktów i reguł przybliżonych w procesie generalizacji informacji geograficznej

A Fiedukowicz - 2017 - repo.pw.edu.pl
It has been 150 years since Sydow called cartographic generalization one of the three “a
reef” of cartography but it still remains one of the key challenges for the cartographic …