Overview

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.

Full Product Details

Author:   Pijush Samui (Associate Professor, Dept. of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India) ,  Barnali Dixon (Professor, School of Geosciences and Director of Geo-spatial Analytics Lab, University of South Florida, St. Petersburg, FL, United States) ,  Dieu Tien Bui (Professor, Geographic Information System group, University of South-Eastern Norway, Norway)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Elsevier Science Publishing Co Inc
Weight:   0.880kg
ISBN:  

9780128205136

ISBN 10:   012820513
Pages:   432
Publication Date:   30 November 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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

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Author Information

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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