Improving Intelligent Decision Making in Urban Planning: Using Machine Learning Algorithms

Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support th...

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Bibliographic Details
Published inInternational journal of business analytics Vol. 8; no. 3; pp. 40 - 58
Main Authors Eom, Sean B, Khediri, Abderrazak, Laouar, Mohamed Ridda
Format Journal Article
LanguageEnglish
Published Montclair IGI Global 01.07.2021
Subjects
Algorithms
Business analytics
Data mining
Decision-making
Machine learning
Multi-agent systems
Algeria
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ISSN2334-4547
2334-4555
DOI10.4018/IJBAN.2021070104

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Summary:Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.
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ISSN:2334-4547
2334-4555
DOI:10.4018/IJBAN.2021070104