Applications of Artificial Intelligence in Mining and Geotechnical Engineering

Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering provides recent advances in mining, geotechnical and geoengineering, as well as applications of artificial intelligence in these areas. It serves as the first book on applications of artificial intelligence in mining, geotechnical and geoengineering, providing an opportunity for researchers, scholars, engineers, practitioners and data scientists from all over the world to understand current developments and applications. Topics covered include slopes, open-pit mines, quarries, shafts, tunnels, caverns, underground mines, metro systems, dams and hydro-electric stations, geothermal energy, petroleum engineering, and radioactive waste disposal. In the geotechnical and geoengineering aspects, topics of specific interest include, but are not limited to, foundation, dam, tunneling, geohazard, geoenvironmental and petroleum engineering, rock mechanics, geotechnical engineering, soil mechanics and foundation engineering, civil engineering, hydraulic engineering, petroleum engineering, engineering geology, etc. Guides readers through the process of gathering, processing, and analyzing datasets specifically tailored for mining, geotechnical, and engineering challenges.Examines the evolution and practical implementation of artificial intelligence models in predicting, forecasting, and optimizing solutions for mining, geotechnical, and engineering problems.Offers cutting-edge methodologies to address the most demanding and complex issues encountered in the fields of mining, geotechnical studies, and engineering. INDICE: A. Overview of AI, learning theory and data analytics techniques1. Overview of artificial intelligence techniques used in the book (US/Europe-based contributors)2. Overview of learning theories used in the book (US/Europe-based contributors)3. Overview of data analytics techniques used in the book (US/Europe-based contributors) B. Applications of artificial intelligence in mining4. Computer vision-based approaches for feature extractions in rock engineering 5. Intelligent optimization of design system for underground space structure of metal mine 6. A comparative study of backbreak distance prediction in the open-pit mine based on support vector regression and three kinds of bio-inspired meta-heuristic algorithms 7. The novel automatic mineral recognition techniques by optical analysis and machine learning 8. Prediction of factor of safety for circular failure slope using support vector regression with two optimization algorithms 9. Application of AI in geochemical anomaly detection 10. Application of AI in mineral prospectivity modeling and mapping 11. Application of AI in estimating mining capital cost 12. Application of AI in forecasting copper prices 13. Application of AI in mine planning 14. Application of AI in reserve and grade estimation of ore 15. Application of AI in predicting blast-induced ground vibration 16. Application of AI in predicting blast-induced air over-pressure 17. Application of AI in predicting blast-induced flyrock 18. Application of AI in predicting blast-induced back-break 19. Application of AI in predicting rock fragmentation 20. Application of AI in estimating ore production of track-haulage system 21. Application of AI in the diagnosis of problems in truck ore transport operation in underground mines 22. Application of AI in predicting air quality in open pit mines 23. Application of AI in predicting rockburst hazards 24. Application of AI in predicting slope stability in open pit mines 25. Application of AI in predicting heavy metals sorption efficiency using mining materials 26. Application of AI in forecasting moment magnitude of micro-earthquakes induced by fault structure and mining activities 27. Application of AI in predicting mine water quality 28. Application of AI for coal mine gas risk assessment 29. Application of AI for predicting hangingwall stability 30. Application of AI for estimating the gross calorific value of coal 31. Application of AI for mapping ground water C. Applications of artificial intelligence in geotechnical and geoengineering32. Hard rock pillar stability prediction using hybrid metaheuristic algorithms and support vector machine approaches based on an updated case histories 33. Application of AI in predicting rock properties during rock drilling operations 34. Application of AI in predicting rock-mechanics parameters 35. Application of AI in predicting rock uniaxial compressive strength 36. Application of AI in mapping landslides 37. Application of AI in predicting diaphragm wall deflection in braced excavation 38. Application of AI in predicting shear strength of tilted angle connectors 39. Application of AI in predicting swelling pressure of expansive soils 40. Application of AI in predicting roadway stability 41. Application of AI in forecasting TBM advance rate 42. Application of AI in estimating the friction angle of clays 43. Application of AI in predicting the compressibility of clay 44. Application of AI in estimating the performance of tunnel boring machines 45. Application of AI in stability classification of discontinuous rock slope 46. Application of AI in rock slope block-toppling modeling and assessment 47. Application of AI in predicting Young's modulus and unconfined compressive strength of rock 48. Application of AI in ground identification of working face 49. Application of AI in predicting ground settlement in tunneling 50. Application of AI in predicting rock geomechanically properties 51.Application of AI in predicting surface settlement induced by earth pressure balance shield tunneling 52. Application of AI in predicting elastic modulus of rocks 53. Application of AI in predicting cohesion of rocks 54. Application of AI in predicting spacing and block volume in discontinuous rock masses using image processing technique

• ISBN: 978-0-443-18764-3
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 496
• Fecha Publicación: 22/11/2023
• Nº Volúmenes: 1
• Idioma: Inglés