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A novel genetic fuzzy markup language and its application to healthy diet assessment

Lee, CS and Wang, MH and Hagras, H and Chen, ZW and Lan, ST and Hsu, CY and Kuo, SE and Kuo, HC and Cheng, HH (2012) 'A novel genetic fuzzy markup language and its application to healthy diet assessment.' International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, 20 (SUPPL.). 247 - 278. ISSN 0218-4885

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In this paper, we present a novel Genetic Fuzzy Markup Language (GFML)-based genetic fuzzy system, including the genetic learning base, the knowledge base and rule base of FML, the fuzzy inference engine, and the genetic learning mechanism. The GFML is applied to the genetic fuzzy system for dealing with the knowledge base, the rule base, and the genetic learning base of the healthy diet domain, including the ingredients and the contained servings of six food categories of some common food in Taiwan. Moreover, the proposed novel system is able to infer the healthy status of human's daily eating. In the proposed system, the domain experts first define the nutrient facts of the common food to construct the fuzzy food ontology. Meanwhile, the involved Taiwanese students of National University of Tainan (NUTN) record their daily meals for a constant period of time. Then, based on the built fuzzy profile ontology, fuzzy food ontology, and fuzzy personal food ontology, a GFML-based genetic fuzzy system is carried out to infer the possibility of dietary healthy level for one-day meals. The experimental results show that the proposed GFML-based genetic fuzzy system gives good results for the healthy diet assessment. © 2012 World Scientific Publishing Company.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 25 Mar 2014 16:42
Last Modified: 28 Apr 2020 23:15

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