ISODATA Clustering Algorithm for Site Selection
DOI: 10.23977/cpcs.2022.060111 | Downloads: 18 | Views: 803
Author(s)
Qing Cai 1, Jinglin Gong 1, Jianfei Huang 1
Affiliation(s)
1 Yangzhou University, Yangzhou, Jiangsu, China
Corresponding Author
Jianfei HuangABSTRACT
This paper mainly solves the problem of site selection. The subject has given the weak coverage area of the existing network according to the coverage of the existing network antenna, and has made a coordinate delineation of the area. By establishing a planning model, we select some of the points to build new base stations, so that the total traffic of the sites covering weak coverage points reaches a predetermined value. This paper establishes the relevant planning model and uses the ISODATA clustering algorithm to solve it.
KEYWORDS
K-Means clustering, ISODATA clustering, Cluster analysis, Goal planningCITE THIS PAPER
Qing Cai, Jinglin Gong, Jianfei Huang, ISODATA Clustering Algorithm for Site Selection. Computing, Performance and Communication Systems (2022) Vol. 6: 66-72. DOI: http://dx.doi.org/10.23977/cpcs.2022.060111.
REFERENCES
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[3] Yue Liang, Si Chen, Yinying Tang. Research on site selection for urban and rural logistics network optimization under FA-kmeans algorithm. Comprehensive Transportation, 2021, 43(05):115-122.
[4] Feibao Song. Improvement of genetic clustering algorithm and its application in gene expression data analysis. Anhui University, 2019.
[5] Litvinenko Natalya, Mamyrbayev Orken, Shayakhmetova Assem, Turdalyuly Mussa. Clusterization by the Kmeans method when K is unknown. ITM Web of Conferences, 2019.
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