On interpretation of graffiti digits and commands for eBooks: Neural fuzzy network and genetic algorithm approach

H. K. Lam, K. F. Leung, S. H. Ling, Hung Fat Frank Leung, P. K S Tam

Research output: Journal article publicationConference articleAcademic researchpeer-review

4 Citations (Scopus)


This paper presents a proposed neural fuzzy network tuned by genetic algorithm (GA). By introducing a switch to each rule, the optimal number of rules can be learned. The membership functions of the neural fuzzy network are also tuned by GA. After training, the proposed neural fuzzy network is employed to interpret graffiti number inputs and commands for Electronic Books (eBooks).
Original languageEnglish
Pages (from-to)443-448
Number of pages6
JournalIEEE International Conference on Fuzzy Systems
Publication statusPublished - 31 Dec 2002
Event2002 IEEE International Conference on Fuzzy Systems: FUZZ-IEEE'02 - Honolulu, HI, United States
Duration: 12 May 200217 May 2002

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

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