Skip to main navigation Skip to search Skip to main content

Facing the problem of small numbers in expert-guided modelling: The case of urban health and planning

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

This study presents a fuzzy logic-based methodology to capture and synthesize expert knowledge in urban health and planning, addressing challenges posed by small sample sizes. A fuzzy inference engine simulates expert consensus using structured semantic categories and consistency weighting. The approach is tested with variables such as fresh fish providers and postal offices in proximity to residences, analyzing their perceived impact on cardiovascular health. Results show the method's capacity to extract nuanced insights while avoiding traditional Delphi limitations.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025
EditorsSemith Ekercin, Mehmet Aktan, Mahendra Gooroochurn, Cafer Çalışka, Emre Arslan, Syed Muzahir Abbas, Bekir Dursun
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-4
Number of pages4
ISBN (Electronic)9798331535629
DOIs
Publication statusPublished - 2025
Event2nd International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025 - Antalya, Turkey
Duration: 7 Aug 20259 Aug 2025

Publication series

NameInternational Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025

Conference

Conference2nd International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2025
Country/TerritoryTurkey
CityAntalya
Period7/08/259/08/25

Fingerprint

Dive into the research topics of 'Facing the problem of small numbers in expert-guided modelling: The case of urban health and planning'. Together they form a unique fingerprint.

Cite this