dc.contributor.author |
Omari, Youcef |
|
dc.contributor.author |
Hamdadou, Djamila |
|
dc.contributor.author |
Mami, Mohammed Amine |
|
dc.date.accessioned |
2023-01-29T19:20:49Z |
|
dc.date.available |
2023-01-29T19:20:49Z |
|
dc.date.issued |
2023-01-29 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
https://journal.uob.edu.bh:443/handle/123456789/4744 |
|
dc.description.abstract |
The Land use management constitutes a multi-dimensional issue affected by a variety of criteria of different significance.
Many decision-makers (DMs) are involved in this type of dilemma, and their preferences are often in dispute. To address these issues,
researchers created a variety of GDSS with various architectures; nevertheless, not all of them can apply artificial intelligence approaches
to mimic human behavior by predciting or classifying solutions. In this work, the authors used a previously designed GDSS named
WIM-GDSS as the foundation for developing a new one with various features; the two systems differ in the prediction model employed.
The proposed system’s prediction module employs a model trained on a multicriteria method known as PROMETHEE II rather than
TOPSIS; the latter method is widely used in the literature and provides more choice and flexibility to the user when expressing
preferences (more subjective parameters than TOPSIS). The paper includes a real case study in territorial planning, in which the proposed
system would manage a group decision-making process for selecting the most suitable vacant zones for housing building. A coordination
protocol will ensure DMs cooperation. The AHP approach will be used to assign criteria weights based on the preferences of DMs. This
system includes a prediction module that predicts solutions rather than calculating them using a prediction model. In order to choose
the optimal model, a comparison study was done between two models: Linear Regression (LR) and Multi Layer Perceptron (MLP).
The results suggest that the MLP model is more suited to PROMETHEE II than the LR model, with a 95% accuracy. Future study will
broaden the trials to include fuzzy logic approaches and completely integrate the proposed system with the geographic information system. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
University of Bahrain |
en_US |
dc.subject |
Group Decision Support System, Multi agent system, Multiple Criteria Analysis, PROMETHEE II GDSS Method, Artificial Intelligence, Prediction Models, Machine Learning, Collaborative Decision |
en_US |
dc.title |
Towards An Intelligent Agent-Based Multi-Criteria Group Decision Support System : A Case Study In Land Use Management |
en_US |
dc.type |
Article |
en_US |
dc.identifier.doi |
http://dx.doi.org/10.12785/ijcds/130125 |
|
dc.volume |
13 |
en_US |
dc.issue |
1 |
en_US |
dc.pagestart |
303 |
en_US |
dc.pageend |
325 |
en_US |
dc.contributor.authoraffiliation |
Laboratory of Informatics of Oran (LIO), Department Computer Science, University of Oran 1, Oran, Algeria |
en_US |
dc.contributor.authoraffiliation |
Laboratory of Research in Industrial Computing and Networks (RIIR), Department Computer Science, University of Oran 1, Oran, Algeria |
en_US |
dc.source.title |
International Journal of Computing and Digital Systems |
en_US |
dc.abbreviatedsourcetitle |
IJCDS |
en_US |