r.mcda.roughset

Generates a MCDA map from several criteria maps using Dominance Rough Set Approach.

r.mcda.roughset [-ln] criteria=name [,name,...] preferences=character decision=name outputMap=string outputTxt=name [--verbose] [--quiet] [--qq] [--ui]

Example:

r.mcda.roughset criteria=name preferences=character decision=name outputMap=string outputTxt=infosys

grass.script.run_command("r.mcda.roughset", criteria, preferences, decision, outputMap, outputTxt="infosys", flags=None, verbose=False, quiet=False, superquiet=False)

Example:

gs.run_command("r.mcda.roughset", criteria="name", preferences="character", decision="name", outputMap="string", outputTxt="infosys")

Parameters

Command linePython (grass.script)

criteria=name [,name,...] [required]
    Name of criteria raster maps
preferences=character [required]
    gain,cost
decision=name [required]
    Name of decision raster map
outputMap=string [required]
    Output classified raster map
outputTxt=name [required]
    Name for output files (base for *.isf and *.rls files)
    Default: infosys
-l
    do not remove single rules in vector format
-n
    compute null value as zero
--help
    Print usage summary
--verbose
    Verbose module output
--quiet
    Quiet module output
--qq
    Very quiet module output
--ui
    Force launching GUI dialog

criteria : str | list[str], required
    Name of criteria raster maps
    Used as: input, raster, name
preferences : str, required
    gain,cost
    Used as: character
decision : str, required
    Name of decision raster map
    Used as: input, raster, name
outputMap : str, required
    Output classified raster map
    Used as: output
outputTxt : str, required
    Name for output files (base for *.isf and *.rls files)
    Used as: output, name
    Default: infosys
flags : str, optional
    Allowed values: l, n
    l
        do not remove single rules in vector format
    n
        compute null value as zero
verbose: bool, optional
    Verbose module output
    Default: False
quiet: bool, optional
    Quiet module output
    Default: False
superquiet: bool, optional
    Very quiet module output
    Default: False

DESCRIPTION

r.mcda.roughset is the python implementation of the dominance rough set approach (Domlem algorithm) in GRASS GIS environment. It requires the following input:
1. the geographical criteria constituting the information system for the rough set analysis; they have to describe environmental, economic or social issues(criteria=name[,name,...]);
2. the preference (preferences=character)for each criteria used in analysis (gain or cost with comma separator)
3. the theme in which areas with the issues to be studied are classified (with crescent preference values) (decision=string).

An information system is generated and Domlem algorithm is applied for extraction a minimal set of rules.

The algorithm builds two text files (outputTxt=name): the first with isf extension for more deep analysis with non geographic software like 4emka and JAMM ; the second file with rls extension hold all the set of rules generate. An output map (outputMap=string)is generated for region classification with the rules finded and the criteria stored in GRASS geodb.

NOTES

The module can work very slowly with high number of criteria and sample. For bug please contact Gianluca Massei (g_mass@libero.it)

REFERENCE

Greco S., Matarazzo B., Slowinski R.: Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129, 1 (2001) 1-47.
Greco S., Matarazzo B., Slowinski R.: Multicriteria classification by dominance-based rough set approach. In: W.Kloesgen and J.Zytkow (eds.), Handbook of Data Mining and Knowledge Discovery, Oxford University Press, New York, 2002.
Greco S., Matarazzo B., Slowinski, R., Stefanowski, J.: An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle. In W. Ziarko, Y. Yao (eds.): Rough Sets and Current Trends in Computing. Lecture Notes in Artificial Intelligence 2005 (2001) 304 - 313. Springer-Verlag
Greco, S., B. Matarazzo, R. Slowinski and J. Stefanowski: Variable consistency model of dominance-based rough set approach. In W.Ziarko, Y.Yao (eds.): Rough Sets and Current Trends in Computing. Lecture Notes in Artificial Intelligence 2005 (2001) 170 - 181. Springer-Verlag
https://en.wikipedia.org/wiki/Dominance-based_rough_set_approach - “Dominance-based rough set approach”
https://fcds.cs.put.poznan.pl/IDSS/software/software_and_projects.htm
- Software from Laboratory of intelligent decision support system in Poznań University of Technology

AUTHORS

Antonio Boggia - Gianluca Massei
Department of Economics and Appraisal - University of Perugia - Italy

SOURCE CODE

Available at: r.mcda.roughset source code (history)
Latest change: Thursday Feb 20 20:36:19 2025 in commit 158e314