Research Repository

A NOVEL GENETIC FUZZY MARKUP LANGUAGE AND ITS APPLICATION TO HEALTHY DIET ASSESSMENT

LEE, CHANG-SHING and WANG, MEI-HUI and HAGRAS, HANI and CHEN, ZHI-WEI and LAN, SHUN-TENG and HSU, CHIN-YUAN and KUO, SU-E and KUO, HUI-CHING and CHENG, HUI-HUA (2012) 'A NOVEL GENETIC FUZZY MARKUP LANGUAGE AND ITS APPLICATION TO HEALTHY DIET ASSESSMENT.' International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 20 (supp02). pp. 247-278. ISSN 0218-4885

Full text not available from this repository.

Abstract

<jats:p> 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. </jats:p>

Item Type: Article
Uncontrolled Keywords: Genetic fuzzy markup language; genetic fuzzy system; fuzzy ontology; healthy diet
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 25 Mar 2014 16:42
Last Modified: 15 Jan 2022 00:28
URI: http://repository.essex.ac.uk/id/eprint/9027

Actions (login required)

View Item View Item