Abstract
This paper presents the rule optimization, tuning of the membership functions, and optimization of the number of fuzzy rules, of a neural-fuzzy network (NFN) using a genetic algorithm (GA). The objectives are achieved by training a proposed NFN with rule switches. The proposed NFN and GA are employed to interpret graffiti number inputs and commands for electronic books (eBooks).
| Original language | English |
|---|---|
| Pages (from-to) | 464-471 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Industrial Electronics |
| Volume | 51 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Apr 2004 |
Keywords
- Electronic books (eBooks)
- Genetic algorithm (GA)
- Neural-fuzzy networks (NFNs)
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Instrumentation