A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications
Article
Article Title | A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications |
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ERA Journal ID | 14562 |
Article Category | Article |
Authors | Sun, Liping (Author), Luo, Yonglong (Author), Ding, Xintao (Author) and Zhang, Ji (Author) |
Journal Title | Computational Intelligence and Neuroscience |
Journal Citation | 2014 |
Number of Pages | 11 |
Year | 2014 |
Publisher | Hindawi Publishing Corporation |
Place of Publication | New York, NY. United States |
ISSN | 1687-5265 |
1687-5273 | |
Digital Object Identifier (DOI) | https://doi.org/10.1155/2014/160730 |
Abstract | An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect. |
Keywords | data mining; spatial clustering analysis; datasets; linear obstacles; planar obstacles; geospatial |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
461301. Coding, information theory and compression | |
460103. Applications in life sciences | |
Byline Affiliations | Anhui Normal University, China |
Centre for Crop Health | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q2x62/a-novel-artificial-immune-algorithm-for-spatial-clustering-with-obstacle-constraint-and-its-applications
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