Title :
Evolutionary fuzzy clustering
Author_Institution :
Fac. of Inf. Sci. & Eng., Canberra Univ., Belconnen, ACT, Australia
fDate :
29 Nov-1 Dec 1995
Abstract :
Genetic algorithms and evolutionary programming methods are employed to perform fuzzy clustering. The experimental results are compared favourably against that of the fuzzy c-means algorithm, and their theoretical justification is given
Keywords :
fuzzy set theory; genetic algorithms; pattern recognition; evolutionary fuzzy clustering; evolutionary programming; experimental results; fuzzy c-means algorithm; fuzzy set theory; genetic algorithms; Australia; Clustering algorithms; Fuzzy sets; Genetic algorithms; Genetic programming; Image recognition; Image segmentation; Iterative algorithms; Partitioning algorithms;
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2759-4
DOI :
10.1109/ICEC.1995.487480
