Replication Data for: Deep neural networks for creating reliable PmP database with a case study in southern California (doi:10.21979/N9/0O380V)

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Part 2: Study Description
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Document Description

Citation

Title:

Replication Data for: Deep neural networks for creating reliable PmP database with a case study in southern California

Identification Number:

doi:10.21979/N9/0O380V

Distributor:

DR-NTU (Data)

Date of Distribution:

2022-03-22

Version:

2

Bibliographic Citation:

Tong, Ping, 2022, "Replication Data for: Deep neural networks for creating reliable PmP database with a case study in southern California", https://doi.org/10.21979/N9/0O380V, DR-NTU (Data), V2

Study Description

Citation

Title:

Replication Data for: Deep neural networks for creating reliable PmP database with a case study in southern California

Identification Number:

doi:10.21979/N9/0O380V

Authoring Entity:

Tong, Ping (Nanyang Technological University)

Software used in Production:

PmPNet

Grant Number:

DMS-1937254

Grant Number:

EAR-2000850

Grant Number:

AcRF Tier-2 Grant (04MNP002073C230)

Grant Number:

AcRF Tier-2 Grant (04MNP002073C230)

Grant Number:

Research Centers of Excellence Initiative (Project Code Number: 04MNS001953A620)

Grant Number:

DMS-1818592

Grant Number:

DMS-2109116

Distributor:

DR-NTU (Data)

Access Authority:

Tong, Ping

Depositor:

Tong, Ping

Date of Deposit:

2022-03-22

Holdings Information:

https://doi.org/10.21979/N9/0O380V

Study Scope

Keywords:

Computer and Information Science, Earth and Environmental Sciences, Mathematical Sciences, Computer and Information Science, Earth and Environmental Sciences, Mathematical Sciences, Deep learning

Abstract:

Southern California PmP phase data expanded by a deep learning technique PmPNet.

Kind of Data:

Seismic Phase Data

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Identification Number:

10.1029/2021JB023830

Bibliographic Citation:

Ding, W., Li, T., Yang, X., Ren, K., & Tong, P. (2022). Deep Neural Networks for Creating Reliable PmP Database With a Case Study in Southern California. Journal of Geophysical Research: Solid Earth, 127(4), e2021JB023830.

Citation

Identification Number:

10356/170958

Bibliographic Citation:

Ding, W., Li, T., Yang, X., Ren, K. & Tong, P. (2022). Deep neural networks for creating reliable PmP database with a case study in Southern California. Journal of Geophysical Research: Solid Earth, 127(4).

Other Study-Related Materials

Label:

PmP_data.txt

Notes:

text/plain

Other Study-Related Materials

Label:

PmP_Net.ipynb

Text:

Source code for PmPNet

Notes:

application/x-ipynb+json

Other Study-Related Materials

Label:

PmP_traveltime_Net.ipynb

Text:

Source code for PmPTraveltimeNet

Notes:

application/x-ipynb+json

Other Study-Related Materials

Label:

Readme.txt

Notes:

text/plain