Basics of Computational Geophysics 1st Edition

Basics of Computational Geophysics 1st Edition – Ebook Instant Download/Delivery ISBN(s): 9780128209011,0128209011

Product details:

• ISBN 10:0128209011
• ISBN 13:9780128209011
• Author: Pijush Samui, Barnali Dixon, Dieu Tien Bui

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.

Table contents:

Chapter 1. Synthetic ground motions of the October 8, 2005 Kashmir earthquake (Mw 7.6): An inference to the site response and seismic hazard of Kashmir basin, NW Himalaya

Chapter 2. Global particle swarm optimization technique in the interpretation of residual magnetic anomalies due to simple geo-bodies with idealized structure

Chapter 3. Emerging techniques to simulate strong ground motion

Chapter 4. Earthquakes: Basics of seismology and computational techniques

Chapter 5. Significance and limit of electrical resistivity survey for detection sub surface cavity: A case study from, Southern Western Ghats, India

Chapter 6. A review on geophysical parameters comparison in Garhwal and Kumaun Himalaya region, India

Chapter 7. Liquefaction susceptibility of high seismic region of Bihar considering fine content

Chapter 8. Evaluating the reliability of various geospatial prediction models in landslide risk zoning

Chapter 9. Fractals and complex networks applied to earthquakes

Chapter 10. Liquefaction as a seismic hazard: Scales, examples and analysis

Chapter 11. Landslide prediction and field monitoring for Darjeeling Himalayas: A case study from Kalimpong

Chapter 11. Landslide prediction and field monitoring for Darjeeling Himalayas: A case study from Kalimpong

Chapter 12. Improvement of shear strength of cohesive soils by additives: A review

Chapter 13. Static stress change from February 6, 2017 (M 5.8) earthquake Northwestern Himalaya, India

Chapter 14. Remote sensing for geology-geophysics

Chapter 15. Prediction of petrophysical parameters using probabilistic neural network technique

Chapter 16. Interpretation and resolution of multiple structures from residual gravity anomaly data and its application to subsurface mineralization

Chapter 17. On fractal based estimations of soil subsidence

Chapter 18. A neural network to predict spectral acceleration

Chapter 19. Prediction of Earth tide

Chapter 20. Time series analysis of hydrometeorological data for the characterization of meltwater storage in glaciers of Garhwal Himalaya

Chapter 21. Trends in frequency and intensity of tropical cyclones in the Bay of Bengal: 1972–2015

Chapter 22. Application of machine learning models in hydrology: Case study of river temperature forecasting in the Drava River using coupled wavelet analysis and adaptive neuro-fuzzy inference systems model

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