{"id":{"repo_id":"brock","oai_identifier":"oai:brocku.scholaris.ca:10464/18774"},"canonical_url":"https://search.dev.ndltd.org/etd/brock/oai:brocku.scholaris.ca:10464/18774","repository":{"repo_id":"brock","name":"Brock University","base_url":"https://brocku.scholaris.ca/server/oai/request"},"display":{"title":"Application of L-Fuzzy Relation to Social Choice Theory","abstract":"In situations like voting, decisions are made based on individual preferences. The majority rule might not always be the best choice for aggregating individual preferences, and individual preferences may be uncertain or partial. For example, someone may prefer a candidate over another, not absolutely, but only up to a certain degree. The objective research of this proposal is to investigate this kind of L-Fuzzy Social Choice Theory, focusing on mathematically modeling personal preferences with uncertainty. It includes implementing visualizations and computations of the three common approaches for modeling individual preferences. The goal is to provide the most general framework in which these three common models of L-fuzzy preference are equivalent.","abstract_html":"In situations like voting, decisions are made based on individual preferences. The majority rule might not always be the best choice for aggregating individual preferences, and individual preferences may be uncertain or partial. For example, someone may prefer a candidate over another, not absolutely, but only up to a certain degree. The objective research of this proposal is to investigate this kind of L-Fuzzy Social Choice Theory, focusing on mathematically modeling personal preferences with uncertainty. It includes implementing visualizations and computations of the three common approaches for modeling individual preferences. The goal is to provide the most general framework in which these three common models of L-fuzzy preference are equivalent.","abstract_has_math":false,"creators":["Osei, Clement Frimpong"],"institution":"Brock University","degree_name":"M.Sc. 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For example, someone may prefer a candidate over another, not absolutely, but only up to a certain degree. The objective research of this proposal is to investigate this kind of L-Fuzzy Social Choice Theory, focusing on mathematically modeling personal preferences with uncertainty. It includes implementing visualizations and computations of the three common approaches for modeling individual preferences. The goal is to provide the most general framework in which these three common models of L-fuzzy preference are equivalent."]},{"key":"dc:title","label":"Title","values":["Application of L-Fuzzy Relation to Social Choice Theory"]}]}],"canonical_facts":{"dc:contributor.department":["Department of Computer Science"],"dc:creator":["Osei, Clement Frimpong"],"dc:date.accessioned":["2024-08-29T18:50:40Z"],"dc:date.available":["2024-08-29T18:50:40Z"],"dc:date.issued":["2024-08-29T18:50:40Z"],"dc:description.abstract":["In situations like voting, decisions are made based on individual preferences. The majority rule might not always be the best choice for aggregating individual preferences, and individual preferences may be uncertain or partial. For example, someone may prefer a candidate over another, not absolutely, but only up to a certain degree. The objective research of this proposal is to investigate this kind of L-Fuzzy Social Choice Theory, focusing on mathematically modeling personal preferences with uncertainty. It includes implementing visualizations and computations of the three common approaches for modeling individual preferences. The goal is to provide the most general framework in which these three common models of L-fuzzy preference are equivalent."],"dc:identifier.uri":["http://hdl.handle.net/10464/18774"],"dc:language.iso":["eng"],"dc:subject":["L-Fuzzy Relations","Social Choice Theory","Preferences","Uncertainty","Mathematical Modeling"],"dc:title":["Application of L-Fuzzy Relation to Social Choice Theory"],"dc:type":["Electronic Thesis or Dissertation"],"thesis:degree_discipline":["Faculty of Mathematics and Science"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.Sc. Computer Science"],"thesis:institution_name":["Brock University"]},"updated_at":"2026-07-24T01:23:12Z"}