DocumentCode
131472
Title
Based on RPCL Object Position Clustering under Cellular Network
Author
Chen Hua-Sha ; Shen Jia-Jie
Author_Institution
Inf. Technol. Center, Shanghai Int. Studies Univ., Shanghai, China
fYear
2014
fDate
10-11 Jan. 2014
Firstpage
163
Lastpage
166
Abstract
Aiming to problem how to cluster object position under cellular network situation, using the method of random selection and position, an improved RPCL (Rival Penalized Competitive Learning) algorithm is designed to handle this question, an improved RPCL algorithm is designed to handle this problem. Though theoretical derivation, the correctness of improved RPCL algorithm is proofed. The correctness of improved RPCL algorithm and theoretical derivation is also verified by experiment.
Keywords
learning (artificial intelligence); pattern clustering; town and country planning; RPCL object position clustering; cellular network situation; city object position clustering; random position method; random selection method; rival penalized competitive learning; smart city; Algorithm design and analysis; Cities and towns; Clustering algorithms; Educational institutions; Neural networks; Training; Vectors; RPCL algorithm; cellular network; position clustering; smart city;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-1-4799-3434-8
Type
conf
DOI
10.1109/ICMTMA.2014.43
Filename
6802659
Link To Document