Basics of Computational Geophysics provides a one-stop, collective resource for practitioners on the different techniques and models in geoscience, their practical applications, and case studies. The reference provides the modeling theory in an easy-to-read format that is verified with onsite models for specific regions and scenarios, including the use of big data and artificial intelligence. This book offers a platform whereby readers will learn theory, practical applications, and the comparison of real-world problems surrounding geomechanics, modeling and optimizations.
Basics of Computational Geophysics provides a one-stop, collective resource for practitioners on the different techniques and models in geoscience, their practical applications, and case studies. The reference provides the modeling theory in an easy-to-read format that is verified with onsite models for specific regions and scenarios, including the use of big data and artificial intelligence. This book offers a platform whereby readers will learn theory, practical applications, and the comparison of real-world problems surrounding geomechanics, modeling and optimizations.
Part I: COMPUTATION & GEOPHYSICS APPLICATIONS
1. Synthetic ground motions of the 2005 Kashmir M7.6 earthquake at
the bedrock and at surface using stochastic dynamic finite fault
modelling with a dynamic corner
Hamid Sana
2. Global particle swarm optimization technique in the
interpretation of residual magnetic anomalies due to simple
geo-bodies with idealized structure
Arkoprovo Biswas and Anand Singh
3. Emerging Techniques to Simulate Strong Ground Motion
Sandeep Arora, Parveen Kumar and A. Joshi
4. Earthquakes: Basics of seismology and seismic computational
techniques
Naresh Kumar Sr., Devajit Hazarika Sr. and Kalachand Sain
5. Significance and limit of electrical resistivity survey for
detection sub surface cavity: a case study from, Southern Western
Ghats, India
Mayank Joshi, Alka Gond, Prasobh. P. Rajan, B. S. S, Padma Rao B
and Vivekanandan Nandakumar
6. A review on Geophysical parameters comparison in Garhwal and
Kumaun Himalaya region, India
Sandeep Arora and Parveen Kumar
7. Liquefaction Susceptibility of High Seismic region of Bihar
considering Fine Content
Sunita Kumari and Sufyan Ghani
8. Evaluating the reliability of various geospatial prediction
models in landslide risk zoning
Chalantika L. Salui
9. Fractals and Complex networks Applied to Earthquakes
Denisse Pasten
10. Liquefaction as a seismic hazard: scales, examples and
analysis
Hamid Sana
11. Landslide Prediction and Field Monitoring for Darjeeling
Himalayas: A case study from Kalimpong
Neelima Satyam
12. Improvement of Shear Strength of Cohesive Soils by Additives: A
Review
Amir H. Gandomi and Tamur Salik
13. Static stress change from 6 February, 2017 (M 5.8) earthquake
Northwestern Himalaya, India
Mahesh prasad Parija, Arkoprovo Biswas and Shubhasmita Biswal
14. Remote Sensing for Geology-Geophysics
Surajit Panda and Krishnendu Banerjee
PART II: COMPUTATION & GEOSCIENCE APPLICATIONS
15. Prediction of Petrophysical Parameters using Probabilistic
Neural NetworkTechnique
Nagendra Pratap Singh
16. Interpretation and Resolution of multiple structures from
residual gravity anomaly data and application to mineral
exploration
Arkoprovo Biswas
17. On fractal based estimations of soil subsidence.
Tatyana P. Mokritskaya and Anatolii Tushev
18. A Neural Network to predict spectral acceleration
Amir H. Gandomi, Ali R. Kashani, Mohsen Akhani and Charles V.
Camp
19. Body tide prediction
Sung-Ho Na
20. Time series analysis of hydrometeorological data for the
characterization of meltwater storage in glaciers of Garhwal
Himalaya
Amit Kumar, Akshaya Verma, Rakesh Bhambri and Kalachand Sain
21. Trends in Frequency and Intensity of Tropical Cyclones in the
Bay of Bengal: 1972-2015
OMVIR SINGH and Pankaj Bhardwaj
22. Application of machine learning models in hydrology: case study
of stream temperature forecasting in the Drava River using coupled
wavelet analysis and adaptive neuro-fuzzy inference systems
model
Senlin Zhu, Marijana Hadzima-Nyarko and Ognjen Bonacci
Dr. Samui is an Associate Professor in the Department of Civil
Engineering at NIT Patna, India. He received his PhD in
Geotechnical Engineering from the Indian Institute of Science
Bangalore, India, in 2008. His research interests include
geohazard, earthquake engineering, concrete technology, pile
foundation and slope stability, and application of AI for solving
different problems in civil engineering. Dr. Samui is a repeat
Elsevier editor but also a prolific contributor to journal papers,
book chapters, and peer-reviewed conference proceedings.
Barnali Dixon is a professor and executive director of Initiative
on Coastal Resilience and Adaptation (iCAR) and the director of
Geospatial Analytics lab (G-SAL) at the University of South
Florida. Her research interests include the development and
application of spatially integrated decision support tools (SDST)
using GIS, GPS and remote sensing tools for modeling and managing
soil, land use and land-water interfaces (terrestrial sources and
aquatics sinks, including coastal waters) using approximation
tools. She is particularly interested in transdisciplinary modeling
of land-water interface under climate change in the context of
planning, adaptation, and resilience. I have secured over $1.5
million in funding, published 50+ refereed publications, nineteen
monographs, and technical reports. Dieu Tien Bui is Professor in
GIS, in the Department of Business and IT at the University of
South-Eastern Norway, Norway. He obtained a Master of Engineering,
at Hanoi University of Mining and Geology, Hanoi, Vietnam, a PhD at
the Department of Mathematical Sciences and Technology (IMT),
Norwegian University, and was postdoctoral researcher in the same
department. His research interests include GIS, remote sensing,
artificial intelligence and machine learning. He published journal
and review articles, and book chapters. .
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