Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018)

Application of Incremental Updating Association Mining Algorithm in Geological Disasters System

Authors
Wang Jianguo, Zhu Ying
Corresponding Author
Wang Jianguo
Available Online April 2018.
DOI
10.2991/icsnce-18.2018.18How to use a DOI?
Keywords
Inverted Index Tree; Geological Disaster System; Frequent Item Sets; Association Rules
Abstract

Aiming at the problems of low efficiency, low cost of time and space, this paper proposes an algorithm to update the association mining of the inverted index tree. The algorithm combines the inverted index technology with the tree structure. When the data in the database is continuously updated, it can scan only the newly added part of the database, without having to scan the original database to count the number of transaction items. The optimal threshold predicted by Newton's interpolation formula is compared with this frequency to get frequent item sets. Then, the confidence level is calculated for the combinations of different item sets in frequent item sets, and the correlation rules are obtained, and the correlation analysis of the rules is carried out to obtain a more realistic association rule. The inverted index tree updating association mining algorithm was applied to the data analysis of geological hazards monitoring system. One year data record of rainfall, groundwater level, soil water content and topography data was selected as the experimental data set. Compared with the IUAR algorithm, it is found that the inverted index tree updating association mining algorithm has some improvements in memory consumption and efficiency. The experimental results show that when the minimum support of IUAR algorithm remains unchanged, the number of transaction records is the same as the amount of new data, and Inverted Index Tree Incremental Updating Association Mining Algorithm takes less than 2/5 of the IUAR algorithm. When the number of transaction records and the amount of new data remain unchanged and IUAR algorithm support changes, the Inverted Index Tree Incremental Updating Association Mining Algorithm memory consumption is much smaller than IUAR algorithm. In the process of experiment, according to the results of the Inverted Index Tree Incremental Updating Association Mining Algorithm, the association rules are obtained and the correlation is judged. The strong association rules are used to set the alarm threshold of the geological disaster monitoring system.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018)
Series
Advances in Computer Science Research
Publication Date
April 2018
ISBN
10.2991/icsnce-18.2018.18
ISSN
2352-538X
DOI
10.2991/icsnce-18.2018.18How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wang Jianguo
AU  - Zhu Ying
PY  - 2018/04
DA  - 2018/04
TI  - Application of Incremental Updating Association Mining Algorithm in Geological Disasters System
BT  - Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018)
PB  - Atlantis Press
SP  - 84
EP  - 92
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsnce-18.2018.18
DO  - 10.2991/icsnce-18.2018.18
ID  - Jianguo2018/04
ER  -