Integration of interpolation and inference with multi-antecedent rules

Authors Organisations
Type Conference Proceeding (Non-Journal item)
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationProceedings of the 19th UK Workshop on Computational Intelligence
EditorsZhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
Pages377-391
Number of pages15
ISBN (Electronic)9783030299330
DOI
Publication statusE-pub ahead of print - 30 Aug 2019
EventUK Workshop on Computational Intelligence - University of Portsmouth, Portsmouth, United Kingdom of Great Britain and Northern Ireland
Duration: 04 Sep 201905 Sep 2019
Conference number: 19
https://www.ukci2019.port.ac.uk/

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer Nature
Volume1043
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Workshop

WorkshopUK Workshop on Computational Intelligence
Abbreviated titleUKCI 2019
CountryUnited Kingdom of Great Britain and Northern Ireland
CityPortsmouth
Period04 Sep 201905 Sep 2019
Internet address
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Abstract

The efficacious fuzzy rule based systems perform their tasks with either a dense rule base or a sparse rule base. The nature of the rule base decides on whether compositional rule of inference (CRI) or fuzzy rule interpolation (FRI) should be applied. Given a dense rule base where at least one rule exists for every observation, CRI can be effectively and sufficiently employed. For a sparse rule base where rules do not cover all possible observations, FRI is required. Nonetheless, certain observations may be matched partly or completely with any of the existing rules in the sparse rule-base. Such observations can be directly dealt with using CRI and the conclusion can be inferred via firing the matched rule, thereby avoiding extra overheads of interpolation. If no such matching can be found then correct rules should be selected to ensure the accuracy while performing FRI. This paper proposes a generalised approach for the integration of FRI and CRI. It utilises the notion of alpha-cut overlapping to determine the matching degree between rule antecedents and a given observation in order to determine if CRI is to be applied. In the event of no matching rules, the nearest rules will be chosen to derive conclusion using FRI based on the best suitable distance metric among possible alternatives such as the Centre of Gravity, Hausdorff Distance and Earth Mover’s Distance. Comparative results are presented to demonstrate the effectiveness of this integrated approach.