On Interpretation of Graffiti Digits and Commands for eBooks: Neural Fuzzy Network and Genetic Algorithm Approach

− 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). I. INTRODUCTION GA is a powerful random search technique to handle optimization problems [1-2, 5]. This is especially useful for complex optimization problems with a large number of parameters that make global analytical solutions difficult to obtain. It has been widely applied in different areas such as fuzzy control [7-9, 13], path planning [10], greenhouse climate control [11], modeling and classification [12, 18] etc.