Preference learning based decision map algebra: specification and implementation

Ahmed Abubahia; Salem Chakhar; Mihaela Cocea

doi:10.1007/978-3-030-29933-0_29

Preference learning based decision map algebra: specification and implementation

Ahmed Abubahia, Salem Chakhar, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

153 Downloads (Pure)

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.

Original language	English
Title of host publication	Advances in Computational Intelligence Systems
Subtitle of host publication	Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
Editors	Zhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
Place of Publication	Cham, Switzerland
Publisher	Springer International Publishing
Pages	342-353
Number of pages	12
Volume	1043
Edition	1
ISBN (Electronic)	978-3-030-29933-0
ISBN (Print)	978-3-030-29932-3
DOIs	https://doi.org/10.1007/978-3-030-29933-0_29
Publication status	Published - Jan 2020
Event	19th UK Workshop on Computational Intelligence - Portsmouth, United Kingdom Duration: 4 Sept 2019 → 5 Sept 2019 Conference number: 19 https://www.ukci2019.port.ac.uk/

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	1043
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Workshop

Workshop	19th UK Workshop on Computational Intelligence
Abbreviated title	UKCI 2019
Country/Territory	United Kingdom
City	Portsmouth
Period	4/09/19 → 5/09/19
Other	The 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	https://www.ukci2019.port.ac.uk/

Keywords

Decision Map Algebra
Preference learning
Spatial modelling
Multicriteria modelling

Access to Document

10.1007/978-3-030-29933-0_29

dma_ ukci_2019_cr
The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-29933-0_29.
Accepted author manuscript (Post-print), 2.05 MB

https://link.springer.com/chapter/10.1007/978-3-030-29933-0_29

Cite this

Abubahia, A., Chakhar, S., & Cocea, M. (2020). Preference learning based decision map algebra: specification and implementation. In Z. Ju, L. Yang, C. Yang, A. Gegov, & D. Zhou (Eds.), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK (1 ed., Vol. 1043, pp. 342-353). (Advances in Intelligent Systems and Computing; Vol. 1043). Springer International Publishing. https://doi.org/10.1007/978-3-030-29933-0_29

Abubahia, Ahmed ; Chakhar, Salem ; Cocea, Mihaela. / Preference learning based decision map algebra: specification and implementation. Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. editor / Zhaojie Ju ; Longzhi Yang ; Chenguang Yang ; Alexander Gegov ; Dalin Zhou. Vol. 1043 1. ed. Cham, Switzerland : Springer International Publishing, 2020. pp. 342-353 (Advances in Intelligent Systems and Computing).

@inproceedings{ce12869a481f4407aac2aa0ebaf38882,

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.",

keywords = "Decision Map Algebra, Preference learning, Spatial modelling, Multicriteria modelling",

author = "Ahmed Abubahia and Salem Chakhar and Mihaela Cocea",

year = "2020",

month = jan,

doi = "10.1007/978-3-030-29933-0_29",

language = "English",

isbn = "978-3-030-29932-3",

volume = "1043",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer International Publishing",

pages = "342--353",

editor = "Zhaojie Ju and Longzhi Yang and Chenguang Yang and Alexander Gegov and Dalin Zhou",

booktitle = "Advances in Computational Intelligence Systems",

edition = "1",

note = "19th UK Workshop on Computational Intelligence, UKCI 2019 ; Conference date: 04-09-2019 Through 05-09-2019",

url = "https://www.ukci2019.port.ac.uk/",

}

Abubahia, A, Chakhar, S & Cocea, M 2020, Preference learning based decision map algebra: specification and implementation. in Z Ju, L Yang, C Yang, A Gegov & D Zhou (eds), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. 1 edn, vol. 1043, Advances in Intelligent Systems and Computing, vol. 1043, Springer International Publishing, Cham, Switzerland , pp. 342-353, 19th UK Workshop on Computational Intelligence, Portsmouth, United Kingdom, 4/09/19. https://doi.org/10.1007/978-3-030-29933-0_29

Preference learning based decision map algebra: specification and implementation. / Abubahia, Ahmed; Chakhar, Salem ; Cocea, Mihaela.
Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. ed. / Zhaojie Ju; Longzhi Yang; Chenguang Yang; Alexander Gegov; Dalin Zhou. Vol. 1043 1. ed. Cham, Switzerland : Springer International Publishing, 2020. p. 342-353 (Advances in Intelligent Systems and Computing; Vol. 1043).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Preference learning based decision map algebra: specification and implementation

AU - Abubahia, Ahmed

AU - Chakhar, Salem

AU - Cocea, Mihaela

N1 - Conference code: 19

PY - 2020/1

Y1 - 2020/1

N2 - 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.

AB - 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.

KW - Decision Map Algebra

KW - Preference learning

KW - Spatial modelling

KW - Multicriteria modelling

U2 - 10.1007/978-3-030-29933-0_29

DO - 10.1007/978-3-030-29933-0_29

M3 - Conference contribution

SN - 978-3-030-29932-3

VL - 1043

T3 - Advances in Intelligent Systems and Computing

SP - 342

EP - 353

BT - Advances in Computational Intelligence Systems

A2 - Ju, Zhaojie

A2 - Yang, Longzhi

A2 - Yang, Chenguang

A2 - Gegov, Alexander

A2 - Zhou, Dalin

PB - Springer International Publishing

CY - Cham, Switzerland

T2 - 19th UK Workshop on Computational Intelligence

Y2 - 4 September 2019 through 5 September 2019

ER -

Abubahia A, Chakhar S , Cocea M. Preference learning based decision map algebra: specification and implementation. In Ju Z, Yang L, Yang C, Gegov A, Zhou D, editors, Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. 1 ed. Vol. 1043. Cham, Switzerland : Springer International Publishing. 2020. p. 342-353. (Advances in Intelligent Systems and Computing). Epub 2019 Aug 30. doi: 10.1007/978-3-030-29933-0_29

Preference learning based decision map algebra: specification and implementation

Abstract

Publication series

Workshop

Keywords

Access to Document

Fingerprint

Cite this