Uncertainty and incompleteness analysis using the rimer approach for urban regeneration processes: The case of the greater Belfast region

Alberto Calzada, Jun Liu, Hui Wang, Anil Kashyap

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Urban regeneration (DR) projects involve a crucial decision-making process that contains a great amount of quantitative and qualitative data including socio-economic processes, policies, expert judgments, stakeholders' opinions, etc. A number of authorities and research studies have used different decision support techniques including Geographic Information Systems (GIS) to approach urban planning decision problems. However, how to handle the uncertainty and incompleteness of information related with many aspects of the UR decision problem is still a challenge issue to be solved. A belief rule-base inference methodology (RIMER) has been recently proposed to handle the uncertainty and incompleteness and incorporate both qualitative and quantitative data within the human decision making procedure. This paper presents an application of the extended RIMER (called RIMER+) to address UR decision problem, where the detailed sensitivity analysis of RIMER+ performance for predicting deprivation measures of the Greater Belfast Region is given by varying the uncertainty and incompleteness levels of the inputs of the system. These case studies are based on real practical data of the Greater Belfast Region in UK. The results demonstrate the positive performance of the RIMER+ method to provide valid and supportive evaluation results, and at the same time to measure the incompleteness and uncertainty range as a reflection of reality as additional support information to help decision making. These positive results indicate that RIMER+ can provide a well-established base to implement further research with combination with GIS to tackle the UR decision problem.

    Original languageEnglish
    Title of host publicationProceedings of 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
    Pages928-934
    Number of pages7
    DOIs
    Publication statusPublished - 2012
    Event2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012 - Xian, Shaanxi, China
    Duration: 15 Jul 201217 Jul 2012

    Publication series

    NameProceedings - International Conference on Machine Learning and Cybernetics
    Volume3
    ISSN (Print)2160-133X
    ISSN (Electronic)2160-1348

    Conference

    Conference2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
    CountryChina
    CityXian, Shaanxi
    Period15/07/1217/07/12

    Keywords

    • Belief rule-base
    • Decision making
    • Decision support system
    • Information incompleteness
    • Spatial decision making
    • Uncertainty
    • Urban regeneration

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