Prediction of Tropical Cyclones’ Characteristic Factors on Hainan Island Using Data Mining Technology

Joint Authors

Gao, Wen-Sheng
Zhou, Ruixu
Zhang, Bowen
Fu, Xianggan
Chen, Qinzhu
Huang, Song
Liang, Yafeng

Source

Advances in Meteorology

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-11-20

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Physics

Abstract EN

A new methodology combining data mining technology with statistical methods is proposed for the prediction of tropical cyclones’ characteristic factors which contain latitude, longitude, the lowest center pressure, and wind speed.

In the proposed method, the best track datasets in the years 1949~2012 are used for prediction.

Using the method, effective criterions are formed to judge whether tropical cyclones land on Hainan Island or not.

The highest probability of accurate judgment can reach above 79%.

With regard to TCs which are judged to land on Hainan Island, related prediction equations are established to effectively predict their characteristic factors.

Results show that the average distance error is improved compared with the National Meteorological Centre of China.

American Psychological Association (APA)

Zhou, Ruixu& Gao, Wen-Sheng& Zhang, Bowen& Fu, Xianggan& Chen, Qinzhu& Huang, Song…[et al.]. 2014. Prediction of Tropical Cyclones’ Characteristic Factors on Hainan Island Using Data Mining Technology. Advances in Meteorology،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1034221

Modern Language Association (MLA)

Zhou, Ruixu…[et al.]. Prediction of Tropical Cyclones’ Characteristic Factors on Hainan Island Using Data Mining Technology. Advances in Meteorology No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1034221

American Medical Association (AMA)

Zhou, Ruixu& Gao, Wen-Sheng& Zhang, Bowen& Fu, Xianggan& Chen, Qinzhu& Huang, Song…[et al.]. Prediction of Tropical Cyclones’ Characteristic Factors on Hainan Island Using Data Mining Technology. Advances in Meteorology. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1034221

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1034221