Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

An Apriori Based Algorithm Associated Point Line Pattern Applied in Seismic Spatial Data

Authors
Yuan Zhou, Lianxiong Gao
Corresponding Author
Yuan Zhou
Available Online January 2016.
DOI
10.2991/icaita-16.2016.47How to use a DOI?
Keywords
spatial datamining; seismic spatial data; probalistic
Abstract

earthquake data in spatial database include two typical types point and line feature, this paper propose an algorithm based on apriori for analysis spatial association pattern during point and line feature, and description algorithm process. since the algorithm is a probability-based mining algorithm, it apply in spatial database of seismic spatial database of Yunnan province china for analysis correlation of point and line pattern. The algorithm have certain significance for analysis spatial probabilistic and spatial reasoning for seismic spatial data.

Copyright
© 2016, 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 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
10.2991/icaita-16.2016.47
ISSN
1951-6851
DOI
10.2991/icaita-16.2016.47How to use a DOI?
Copyright
© 2016, 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  - Yuan Zhou
AU  - Lianxiong Gao
PY  - 2016/01
DA  - 2016/01
TI  - An Apriori Based Algorithm Associated Point Line Pattern Applied in Seismic Spatial Data
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 187
EP  - 190
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.47
DO  - 10.2991/icaita-16.2016.47
ID  - Zhou2016/01
ER  -