DocumentCode
2620907
Title
An evolution strategy for the induction of fuzzy finite-state automata
Author
Zhiwen, Mo ; Min, Wan ; Lan, Shu
Author_Institution
Dept. of Appl. Math, Southwest Jiaotong Univ., China
Volume
2
fYear
2005
fDate
25-27 July 2005
Firstpage
579
Abstract
This paper presents an evolution strategy used to infer fuzzy finite-state automata from examples of a fuzzy language. We describe the fitness function of an generated automata with respect to a set of examples of a fuzzy language, the representation of the transition of the automata as well as the output of the states in the evolution strategy and the simple mutation operators that work on these representations. Results are reported on the inference of a fuzzy language.
Keywords
evolutionary computation; finite state machines; fuzzy set theory; inference mechanisms; evolution strategy; fitness function; fuzzy finite-state automata; fuzzy language inference; mutation operator; Automata; Educational institutions; Electrical capacitance tomography; Fuzzy sets; Genetic mutations; Induction generators; Paper technology; Pattern recognition; Speech analysis; Training data; evolution strategy; fitness; fuzzy finite state automata; generalization; mutation;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2005 IEEE International Conference on
Print_ISBN
0-7803-9017-2
Type
conf
DOI
10.1109/GRC.2005.1547358
Filename
1547358
Link To Document