Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Prediction of Terrorist Attacks in China based on BP improved Algorithm and GTD

Authors
Le Hong
Corresponding Author
Le Hong
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.65How to use a DOI?
Keywords
BP network; GTD sample; number of terrorist attacks; prediction.
Abstract
Due to the different national conditions, the driving forces and factors of national terrorist attacks vary. Therefore, this paper takes GTD China sample data as the research object to study and predict. The prediction process is as follows: On the basis of the BP network-based model for predicting the most dangerous areas, combined with the GTD sample data, the best number of nodes in the implicit layer of the prediction model is automatically selected by combining the empirical formula with the MATLAB program. Three improved BP algorithms are used to train the network model. The results show that the training error of Levenburg Marquardt algorithm is minimal and the convergence speed is fastest. Through the training and simulation of the model, it is proved that the model has high precision and can meet the requirement of practical application.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.65How 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  - Le Hong
PY  - 2019/04
DA  - 2019/04
TI  - Prediction of Terrorist Attacks in China based on BP improved Algorithm and GTD
PB  - Atlantis Press
SP  - 403
EP  - 407
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.65
DO  - https://doi.org/10.2991/icmeit-19.2019.65
ID  - Hong2019/04
ER  -