Description
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.- Covers various advanced computational techniques for solving different problems in geophysics, including the use of Big Data and artificial intelligence- Includes case studies that provide examples surrounding practical applications- Provides an assessment of the capabilities of commercial software
Table of Contents
Part I: COMPUTATION & GEOPHYSICS APPLICATIONS1. 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 cornerHamid Sana2. Global particle swarm optimization technique in the interpretation of residual magnetic anomalies due to simple geo-bodies with idealized structureArkoprovo Biswas and Anand Singh3. Emerging Techniques to Simulate Strong Ground MotionSandeep Arora, Parveen Kumar and A. Joshi4. Earthquakes: Basics of seismology and seismic computational techniquesNaresh Kumar Sr., Devajit Hazarika Sr. and Kalachand Sain5. Significance and limit of electrical resistivity survey for detection sub surface cavity: a case study from, Southern Western Ghats, IndiaMayank Joshi, Alka Gond, Prasobh. P. Rajan, B. S. S, Padma Rao B and Vivekanandan Nandakumar6. A review on Geophysical parameters comparison in Garhwal and Kumaun Himalaya region, IndiaSandeep Arora and Parveen Kumar7. Liquefaction Susceptibility of High Seismic region of Bihar considering Fine ContentSunita Kumari and Sufyan Ghani8. Evaluating the reliability of various geospatial prediction models in landslide risk zoningChalantika L. Salui9. Fractals and Complex networks Applied to EarthquakesDenisse Pasten10. Liquefaction as a seismic hazard: scales, examples and analysisHamid Sana11. Landslide Prediction and Field Monitoring for Darjeeling Himalayas: A case study from KalimpongNeelima Satyam12. Improvement of Shear Strength of Cohesive Soils by Additives: A ReviewAmir H. Gandomi and Tamur Salik13. Static stress change from 6 February, 2017 (M 5.8) earthquake Northwestern Himalaya, IndiaMahesh prasad Parija, Arkoprovo Biswas and Shubhasmita Biswal14. Remote Sensing for Geology-GeophysicsSurajit Panda and Krishnendu BanerjeePART II: COMPUTATION & GEOSCIENCE APPLICATIONS15. Prediction of Petrophysical Parameters using Probabilistic Neural NetworkTechniqueNagendra Pratap Singh16. Interpretation and Resolution of multiple structures from residual gravity anomaly data and application to mineral explorationArkoprovo Biswas17. On fractal based estimations of soil subsidence.Tatyana P. Mokritskaya and Anatolii Tushev18. A Neural Network to predict spectral accelerationAmir H. Gandomi, Ali R. Kashani, Mohsen Akhani and Charles V. Camp19. Body tide predictionSung-Ho Na20. Time series analysis of hydrometeorological data for the characterization of meltwater storage in glaciers of Garhwal HimalayaAmit Kumar, Akshaya Verma, Rakesh Bhambri and Kalachand Sain21. Trends in Frequency and Intensity of Tropical Cyclones in the Bay of Bengal: 1972-2015OMVIR SINGH and Pankaj Bhardwaj22. 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 modelSenlin Zhu, Marijana Hadzima-Nyarko and Ognjen Bonacci
