Peak ground acceleration prediction using supervised machine learning algorithm for the seismically hazardous Kachchh rift zone, Gujarat, India

Peak ground acceleration prediction using artificial neural networks for Kachchh, Gujarat, India

(2022) Prantik Mandal   NATURAL HAZARDS

Stochastic Simulation of Strong Ground Motions From Two M > 5 Uttarakhand Earthquakes

(2021) Nitin Sharma et al.   Frontiers in Earth Science

A machine learning framework for multi-hazards modeling and mapping in a mountainous area

(2020) Saleh Yousefi et al.   Scientific Reports

Stochastic earthquake source model for ground motion simulation

(2019) P. R. Lekshmy et al.   Earthquake Engineering and Engineering Vibration

Machine learning for data-driven discovery in solid Earth geoscience

(2019) Karianne J. Bergen et al.   SCIENCE

Earthquake hazard potential of Indo-Gangetic Foredeep: its seismotectonism, hazard, and damage modeling for the cities of Patna, Lucknow, and Varanasi

(2019) Sankar Kumar Nath et al.   JOURNAL OF SEISMOLOGY

The Generic Mapping Tools Version 6

(2019) P. Wessel et al.   GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS

Seismic attenuation model using artificial neural networks

(2019) M.C. Raghucharan et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Relocations and local earthquake tomography: Implications toward the mafic pluton induced crustal seismicity in Kachchh, Gujarat, India, for last 18 years

(2019) Prantik Mandal   JOURNAL OF ASIAN EARTH SCIENCES

Strong Correlation between Stress Drop and Peak Ground Acceleration for Recent M 1–4 Earthquakes in the San Francisco Bay Area

(2018) Daniel T. Trugman et al.   BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA

Machine Learning in Seismology: Turning Data into Insights

(2018) Qingkai Kong et al.   SEISMOLOGICAL RESEARCH LETTERS

Site-Condition Proxies, Ground Motion Variability, and Data-Driven GMPEs: Insights from the NGA-West2 and RESORCE Data Sets

(2016) Boumédiène Derras et al.   EARTHQUAKE SPECTRA

Summary of the ASK14 Ground Motion Relation for Active Crustal Regions

(2014) Norman A. Abrahamson et al.   EARTHQUAKE SPECTRA

NGA-West2 Research Project

(2014) Yousef Bozorgnia et al.   EARTHQUAKE SPECTRA

Towards fully data driven ground-motion prediction models for Europe

(2013) Boumédiène Derras et al.   Bulletin of Earthquake Engineering

Ground motion prediction equation considering combined dataset of recorded and simulated ground motions

(2013) P. Anbazhagan et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Adapting the Neural Network Approach to PGA Prediction: An Example Based on the KiK-net Data

(2012) B. Derras et al.   BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA

Ground Motion Synthesis and Seismic Scenario in Guwahati City--A Stochastic Approach

(2009) S. K. Nath et al.   SEISMOLOGICAL RESEARCH LETTERS

NGA Ground Motion Model for the Geometric Mean Horizontal Component of PGA, PGV, PGD and 5% Damped Linear Elastic Response Spectra for Periods Ranging from 0.01 to 10 s

(2008) Kenneth W. Campbell et al.   EARTHQUAKE SPECTRA

Summary of the Abrahamson & Silva NGA Ground-Motion Relations

(2008) Norman Abrahamson et al.   EARTHQUAKE SPECTRA

Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 sand 10.0 s

(2008) David M. Boore et al.   EARTHQUAKE SPECTRA

Vs30: Proxy for Seismic Amplification?

(2008) S. Castellaro et al.   SEISMOLOGICAL RESEARCH LETTERS

Surface-to-base amplification evaluated from KiK-net vertical array strong motion records

(2008) Takaji Kokusho et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Ground motion estimation at Guwahati city for an Mw 8.1 earthquake in the Shillong plateau

(2007) S.T.G. Raghu Kanth et al.   TECTONOPHYSICS