Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh

Sarker Md Tanzim; Sadia Yeasmin; Muhammad Abrar Hussain; T. M. Rezoan Tamal; Rashidul Hasan; Tanjir Rahman; Rashedur M. Rahman

doi:10.1007/978-3-319-91189-2_36

Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh

Sarker Md Tanzim
, Sadia Yeasmin
, Muhammad Abrar Hussain
, T. M. Rezoan Tamal
, Rashidul Hasan
, Tanjir Rahman
, Rashedur M. Rahman^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The paper demonstrates the use of clustering to find different sensitive seismic zones and time series for the earthquake hazard prediction. Anticipating seismic activities using previous history data is obtained by applying hierarchical, k-means and density based clustering. Data is collected first and then clustered. Finally, the clustered data is used to obtain the different seismic zones on map. On the top of that data is used in linear regression to build a predictive model for forecasting upcoming earthquakes’ magnitudes for different regions in and nearby areas of Bangladesh.

Original language	English
Title of host publication	Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018
Editors	Radek Silhavy
Publisher	Springer Verlag
Pages	364-373
Number of pages	10
ISBN (Print)	9783319911885
DOIs	https://doi.org/10.1007/978-3-319-91189-2_36
State	Published - 2019
Externally published	Yes
Event	7th Computer Science On-line Conference, CSOC 2018 - Zlin, Czech Republic Duration: 25 Apr 2018 → 28 Apr 2018

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	764
ISSN (Print)	2194-5357

Conference

Conference	7th Computer Science On-line Conference, CSOC 2018
Country/Territory	Czech Republic
City	Zlin
Period	25/04/18 → 28/04/18

Bibliographical note

Publisher Copyright:
© 2019, Springer International Publishing AG, part of Springer Nature.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Clustering
Data mining
Earthquakes
Forecasting
Frequent pattern
Magnitudes
Regression
WEKA

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-91189-2_36

Cite this

Md Tanzim, S., Yeasmin, S., Hussain, M. A., Rezoan Tamal, T. M., Hasan, R., Rahman, T., & Rahman, R. M. (2019). Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh. In R. Silhavy (Ed.), Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018 (pp. 364-373). (Advances in Intelligent Systems and Computing; Vol. 764). Springer Verlag. https://doi.org/10.1007/978-3-319-91189-2_36

Md Tanzim, Sarker ; Yeasmin, Sadia ; Hussain, Muhammad Abrar et al. / Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh. Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018. editor / Radek Silhavy. Springer Verlag, 2019. pp. 364-373 (Advances in Intelligent Systems and Computing).

@inproceedings{8250b3a3b7194202a52f584780f8749c,

title = "Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh",

abstract = "The paper demonstrates the use of clustering to find different sensitive seismic zones and time series for the earthquake hazard prediction. Anticipating seismic activities using previous history data is obtained by applying hierarchical, k-means and density based clustering. Data is collected first and then clustered. Finally, the clustered data is used to obtain the different seismic zones on map. On the top of that data is used in linear regression to build a predictive model for forecasting upcoming earthquakes{\textquoteright} magnitudes for different regions in and nearby areas of Bangladesh.",

keywords = "Clustering, Data mining, Earthquakes, Forecasting, Frequent pattern, Magnitudes, Regression, WEKA",

author = "\{Md Tanzim\}, Sarker and Sadia Yeasmin and Hussain, \{Muhammad Abrar\} and \{Rezoan Tamal\}, \{T. M.\} and Rashidul Hasan and Tanjir Rahman and Rahman, \{Rashedur M.\}",

note = "Publisher Copyright: {\textcopyright} 2019, Springer International Publishing AG, part of Springer Nature.; 7th Computer Science On-line Conference, CSOC 2018 ; Conference date: 25-04-2018 Through 28-04-2018",

year = "2019",

doi = "10.1007/978-3-319-91189-2\_36",

language = "English",

isbn = "9783319911885",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "364--373",

editor = "Radek Silhavy",

booktitle = "Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018",

address = "Germany",

}

Md Tanzim, S, Yeasmin, S, Hussain, MA, Rezoan Tamal, TM, Hasan, R, Rahman, T & Rahman, RM 2019, Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh. in R Silhavy (ed.), Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018. Advances in Intelligent Systems and Computing, vol. 764, Springer Verlag, pp. 364-373, 7th Computer Science On-line Conference, CSOC 2018, Zlin, Czech Republic, 25/04/18. https://doi.org/10.1007/978-3-319-91189-2_36

Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh. / Md Tanzim, Sarker; Yeasmin, Sadia; Hussain, Muhammad Abrar et al.
Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018. ed. / Radek Silhavy. Springer Verlag, 2019. p. 364-373 (Advances in Intelligent Systems and Computing; Vol. 764).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh

AU - Md Tanzim, Sarker

AU - Yeasmin, Sadia

AU - Hussain, Muhammad Abrar

AU - Rezoan Tamal, T. M.

AU - Hasan, Rashidul

AU - Rahman, Tanjir

AU - Rahman, Rashedur M.

PY - 2019

Y1 - 2019

N2 - The paper demonstrates the use of clustering to find different sensitive seismic zones and time series for the earthquake hazard prediction. Anticipating seismic activities using previous history data is obtained by applying hierarchical, k-means and density based clustering. Data is collected first and then clustered. Finally, the clustered data is used to obtain the different seismic zones on map. On the top of that data is used in linear regression to build a predictive model for forecasting upcoming earthquakes’ magnitudes for different regions in and nearby areas of Bangladesh.

AB - The paper demonstrates the use of clustering to find different sensitive seismic zones and time series for the earthquake hazard prediction. Anticipating seismic activities using previous history data is obtained by applying hierarchical, k-means and density based clustering. Data is collected first and then clustered. Finally, the clustered data is used to obtain the different seismic zones on map. On the top of that data is used in linear regression to build a predictive model for forecasting upcoming earthquakes’ magnitudes for different regions in and nearby areas of Bangladesh.

KW - Clustering

KW - Data mining

KW - Earthquakes

KW - Forecasting

KW - Frequent pattern

KW - Magnitudes

KW - Regression

KW - WEKA

UR - https://www.scopus.com/pages/publications/85047857163

U2 - 10.1007/978-3-319-91189-2_36

DO - 10.1007/978-3-319-91189-2_36

M3 - Conference contribution

AN - SCOPUS:85047857163

SN - 9783319911885

T3 - Advances in Intelligent Systems and Computing

SP - 364

EP - 373

BT - Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018

A2 - Silhavy, Radek

PB - Springer Verlag

T2 - 7th Computer Science On-line Conference, CSOC 2018

Y2 - 25 April 2018 through 28 April 2018

ER -

Md Tanzim S, Yeasmin S, Hussain MA, Rezoan Tamal TM, Hasan R, Rahman T et al. Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh. In Silhavy R, editor, Artificial Intelligence and Algorithms in Intelligent Systems - Proceedings of 7th Computer Science On-line Conference, 2018. Springer Verlag. 2019. p. 364-373. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-91189-2_36

Analysis of spatial data and time series for predicting magnitude of seismic zones in Bangladesh

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this