TY - GEN
T1 - Outlier detection algorithm based on SOM neural network for spatial series dataset
AU - Liu, Yaxian
AU - Lu, Hui
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - Outlier detection is an important branch of data mining which has been applied in different fields. Facing the multidimensional spatial series dataset containing both isolated and assembled outliers, many existing methods become unsatisfactory or even inapplicable. In this paper, we propose an outlier detection algorithm based on SOM (Self-Organizing Maps) neural network for the spatial series dataset. Firstly, we introduce the principle of the clustering algorithm based on SOM neural network. Secondly, the outlier detection strategy is designed according to the topological distribution of neurons. Finally, in order to verify the effectiveness and reliability of the proposed algorithm, several experiments are performed in this paper. The simulation illustrates that the proposed algorithm based on SOM neural network is very effective and reliable for spatial series dataset.
AB - Outlier detection is an important branch of data mining which has been applied in different fields. Facing the multidimensional spatial series dataset containing both isolated and assembled outliers, many existing methods become unsatisfactory or even inapplicable. In this paper, we propose an outlier detection algorithm based on SOM (Self-Organizing Maps) neural network for the spatial series dataset. Firstly, we introduce the principle of the clustering algorithm based on SOM neural network. Secondly, the outlier detection strategy is designed according to the topological distribution of neurons. Finally, in order to verify the effectiveness and reliability of the proposed algorithm, several experiments are performed in this paper. The simulation illustrates that the proposed algorithm based on SOM neural network is very effective and reliable for spatial series dataset.
KW - Detection strategy
KW - Outlier detection
KW - SOM neural network
KW - Spatial series dataset
UR - https://www.scopus.com/pages/publications/85049798368
U2 - 10.1109/ICACI.2018.8377600
DO - 10.1109/ICACI.2018.8377600
M3 - 会议稿件
AN - SCOPUS:85049798368
T3 - Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
SP - 162
EP - 168
BT - Proceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Advanced Computational Intelligence, ICACI 2018
Y2 - 29 March 2018 through 31 March 2018
ER -