Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

The Research of Meteorological Data Mining Using Discrete Bayesian Networks Classifier Based on Hadoop

Authors
Yongjun Zhang, Jing Sun
Corresponding Author
Yongjun Zhang
Available Online June 2015.
DOI
https://doi.org/10.2991/icecee-15.2015.189How to use a DOI?
Keywords
Bayesian Networks; Predictive Ability; Classified Prediction; Data Mining; Hadoop
Abstract
The method of Native Bayesian classification data mining in weather forecast has some defects, such as there is not independent of each other between predictors, but a certain relevance which results in the decrease of prediction accuracy. This paper explores an improved algorithm which is based on the theory of discrete Bayesian Networks, and combines with Hadoop distributed file system and parallel processing programming models to predict rainfall. The experiments show that the improved algorithm not only makes the classification prediction more reliable but also improves the efficiency greatly. In addition, it provides a solution of huge amounts of data mining in the other fields.
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Proceedings
2015 2nd International Conference on Electrical, Computer Engineering and Electronics
Part of series
Advances in Computer Science Research
Publication Date
June 2015
ISBN
978-94-62520-81-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/icecee-15.2015.189How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yongjun Zhang
AU  - Jing Sun
PY  - 2015/06
DA  - 2015/06
TI  - The Research of Meteorological Data Mining Using Discrete Bayesian Networks Classifier Based on Hadoop
BT  - 2015 2nd International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 996
EP  - 1001
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.189
DO  - https://doi.org/10.2991/icecee-15.2015.189
ID  - Zhang2015/06
ER  -