Establishing site response-based micro-zonation by applying machine learning techniques on ambient noise data: a case study from Northern Potwar Region, Pakistan

S.M.T. Qadri; O.A. Malik

doi:10.1007/s12665-020-09322-7

Establishing site response-based micro-zonation by applying machine learning techniques on ambient noise data: a case study from Northern Potwar Region, Pakistan

S.M.T. Qadri
, O.A. Malik

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Original language	Undefined/Unknown
Journal	Environmental Earth Sciences
DOIs	https://doi.org/10.1007/s12665-020-09322-7
Publication status	Published - 2021

Access to Document

10.1007/s12665-020-09322-7

Cite this

@article{6f43909b01044bb8a32b75751314fe36,

title = "Establishing site response-based micro-zonation by applying machine learning techniques on ambient noise data: a case study from Northern Potwar Region, Pakistan",

author = "S.M.T. Qadri and O.A. Malik",

year = "2021",

doi = "10.1007/s12665-020-09322-7",

language = "Undefined/Unknown",

journal = "Environmental Earth Sciences",

issn = "1866-6280",

}

TY - JOUR

T1 - Establishing site response-based micro-zonation by applying machine learning techniques on ambient noise data: a case study from Northern Potwar Region, Pakistan

AU - Qadri, S.M.T.

AU - Malik, O.A.

PY - 2021

Y1 - 2021

UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85099102096&partnerID=MN8TOARS

U2 - 10.1007/s12665-020-09322-7

DO - 10.1007/s12665-020-09322-7

M3 - Article

SN - 1866-6280

JO - Environmental Earth Sciences

JF - Environmental Earth Sciences

ER -

Establishing site response-based micro-zonation by applying machine learning techniques on ambient noise data: a case study from Northern Potwar Region, Pakistan

Access to Document

Other files and links

Cite this