TY - JOUR
T1 - A knowledge context fuzzy clustering method based on genetic algorithm
AU - Zhang, Faping
AU - Li, Li
AU - Zhou, Cuixiang
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences, 2017.
PY - 2017/12/5
Y1 - 2017/12/5
N2 - A fuzzy clustering method based on genetic algorithm is proposed aiming at the problem of automatic clustering of knowledge context. Firstly, the knowledge context model is constructed to determine the similarity measure of knowledge context. Then the initial clustering centers are obtained based on the density peak method. Then the fuzzy C mean clustering result is solved by genetic algorithm, and the clustering of knowledge context is realized. Finally, the knowledge context clustering of an aircraft part design process is taken as an example to illustrate the effectiveness of the algorithm.
AB - A fuzzy clustering method based on genetic algorithm is proposed aiming at the problem of automatic clustering of knowledge context. Firstly, the knowledge context model is constructed to determine the similarity measure of knowledge context. Then the initial clustering centers are obtained based on the density peak method. Then the fuzzy C mean clustering result is solved by genetic algorithm, and the clustering of knowledge context is realized. Finally, the knowledge context clustering of an aircraft part design process is taken as an example to illustrate the effectiveness of the algorithm.
UR - https://www.scopus.com/pages/publications/85039449075
U2 - 10.1051/matecconf/201713900064
DO - 10.1051/matecconf/201713900064
M3 - Conference article
AN - SCOPUS:85039449075
SN - 2261-236X
VL - 139
JO - MATEC Web of Conferences
JF - MATEC Web of Conferences
M1 - 00064
T2 - 3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017
Y2 - 16 December 2017 through 17 December 2017
ER -