Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application

  • Chang -Shing Lee
  • Mei -Hui Wang
  • Chin -Yuan Hsu
  • Zhi -Wei Chen
Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 301)

Abstract

Nowadays, most people can get enough energy to maintain one-day activity, while few people know whether they eat healthily or not. It is quite important to analyze nutritional facts of foods eaten for those who are losing weight or suffering chronic diseases such as diabetes. However, diet is a problem with a high uncertainty, and it is widely pointed out that classical ontology is not sufficient to deal with imprecise and vague knowledge for some real-world applications like diet. On the other hand, a fuzzy ontology can effectively help handle and process uncertain data and knowledge. This chapter proposes a type-2 fuzzy set and fuzzy ontology for diet application and uses the type-2 fuzzy markup language (T2FML) to describe the knowledge base and rule base of the diet, including ingredients and the contained servings of six food categories of some common foods in Taiwan. The experimental results show that type-2 fuzzy logic system (FLS) performs better than type-1 FLS, proving that type-2 FLS can provide a powerful paradigm to handle the high level of uncertainties present in diet.

Type-2 Fuzzy set Fuzzy Ontology Type-2 Fuzzy Markup Language (T2FML) Type-2 Fuzzy inference mechanism Dietary Healthy Level (DHL) Dietary assessment Balanced diet Fuzzy food ontology Fuzzy personal food ontology T2FML-based fuzzy inference mechanism Percentage of Calories from Carbohydrate (PCC) Percentage of Calories from Protein (PCP) Percentage of Calories from Fat (PCF) Percentage of Caloric Ratio (PCR) Food Group Balance (FGB) 

Notes

Acknowledgments

This work is supported by the National Science Council (NSC) of Taiwan under the grant NSC98-2221-E-024-009-MY3 and 99-2622-E-024-003-CC3. The authors wish to thank Su-E Kuo, Hui-Ching Kuo, and Hui-Hua Chen, for their support with the experimental results.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Chang -Shing Lee
    • 1
  • Mei -Hui Wang
    • 1
  • Chin -Yuan Hsu
    • 2
  • Zhi -Wei Chen
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational University of TainanTainanTaiwan
  2. 2.Chunghwa TelecomTaipeiTaiwan

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