TY - GEN
T1 - Sudden grid-clustering method based on improved multi-variety ant algorithm
AU - Qian, Haizhong
AU - Wu, Fang
AU - Chen, Bo
AU - Liu, Ying
AU - Wang, Jiayao
PY - 2006
Y1 - 2006
N2 - Spatial clustering is important to the application of artificial intelligence in spatial information system. After introducing clustering's basic concept, some shortcomings of current clustering algorithms were analyzed, and the steps of improving on them were given as the following. First, a way of transforming vector data to grid was presented, and a formula of calculating grid-unit's value was defined. Second, three type ants and their mutual-transformation modes were defined, which were used to regulate ants' action so as to improve algorithm's intelligence and agility. Third, based on the grid technique and multi-variety ant algorithm, a new clustering method came into being, and its whole process was expounded. Finally, an example was illustrated for clarifying the theory of this method, and its advantages were pointed out. Analysis indicates that compared with existent clustering algorithms, the method created in this paper satisfies the requirements of speed, intelligence and independence in spatial data clustering.
AB - Spatial clustering is important to the application of artificial intelligence in spatial information system. After introducing clustering's basic concept, some shortcomings of current clustering algorithms were analyzed, and the steps of improving on them were given as the following. First, a way of transforming vector data to grid was presented, and a formula of calculating grid-unit's value was defined. Second, three type ants and their mutual-transformation modes were defined, which were used to regulate ants' action so as to improve algorithm's intelligence and agility. Third, based on the grid technique and multi-variety ant algorithm, a new clustering method came into being, and its whole process was expounded. Finally, an example was illustrated for clarifying the theory of this method, and its advantages were pointed out. Analysis indicates that compared with existent clustering algorithms, the method created in this paper satisfies the requirements of speed, intelligence and independence in spatial data clustering.
KW - Ant colony algorithm
KW - Clustering analysis
KW - Grid
KW - Intelligence
KW - Spatial information system
UR - https://www.scopus.com/pages/publications/34047194854
U2 - 10.1109/WCICA.2006.1713168
DO - 10.1109/WCICA.2006.1713168
M3 - 会议稿件
AN - SCOPUS:34047194854
SN - 1424403324
SN - 9781424403325
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 4209
EP - 4213
BT - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
T2 - 6th World Congress on Intelligent Control and Automation, WCICA 2006
Y2 - 21 June 2006 through 23 June 2006
ER -