Proceedings of the International Conference on Education, Management, Commerce and Society

Application of CNN in the Prediction of Hail Cloudy

Authors
Jinlei Cui, Guodong Li, Wenxia Xu
Corresponding Author
Jinlei Cui
Available Online January 2015.
DOI
10.2991/emcs-15.2015.163How to use a DOI?
Keywords
Cellular Neural Network; Wavelet transform; Prediction; Life feature vector matrix
Abstract

This paper studies on the prediction of the hail. First, Cellular Neural Network method acts on the cloud radar images to extract their edge, The cloud’s contour feature would be more clear; and then, the edge detection would be processed by wavelet transform. Five different coefficients would be found; At last we construct hail cloud life feature vector matrix, explain the problem by matrix form, so as to find the corresponding rules through the five coefficients, after seeking to rules, through the simulation experiment, to achieve the purpose of hail forecast.

Copyright
© 2015, 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 International Conference on Education, Management, Commerce and Society
Series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2015
ISBN
10.2991/emcs-15.2015.163
ISSN
2352-5398
DOI
10.2991/emcs-15.2015.163How to use a DOI?
Copyright
© 2015, 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  - Jinlei Cui
AU  - Guodong Li
AU  - Wenxia Xu
PY  - 2015/01
DA  - 2015/01
TI  - Application of CNN in the Prediction of Hail Cloudy
BT  - Proceedings of the International Conference on Education, Management, Commerce and Society
PB  - Atlantis Press
SP  - 795
EP  - 799
SN  - 2352-5398
UR  - https://doi.org/10.2991/emcs-15.2015.163
DO  - 10.2991/emcs-15.2015.163
ID  - Cui2015/01
ER  -