Intelligence Systems for Earth, Environmental and Planetary Sciences

Methods, Models and Applications

Hossein Bonakdari, Silvio José Gumiere, Hossein Bonakdari, Silvio José Gumiere

• Publisher: Elsevier
• Year: 2024
• ISBN:
  9780443132926
• Topic: Sciences physiques
• Subtopic: Géologie et sciences de la Terre

Intelligence Systems for Earth, Environmental and Planetary Sciences: Methods, Models and Applications provides cutting-edge theory and applications of modern-day artificial intelligence and data science in the Earth, environment, and planetary science fields. The book is divided into three sections: (i) Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets; (ii) Models, detailing model development, data assimilation, and techniques in each field; and (iii) Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives. Intelligence Systems for Earth, Environmental and Planetary Sciences will be of interest to students, academics, and postgraduate professionals in the field of applied sciences, Earth, environmental, and planetary sciences and would also serve as an excellent companion resource to courses studying artificial intelligence applications for theoretical and practical studies in Earth, environmental, and planetary sciences.

• Facilitates the application of artificial intelligence and data science systems to create comprehensive methodologies for analyzing, processing, predicting, and management strategies in the fields of Earth, environment, and planetary science
• Developed with an interdisciplinary framework, with an aim to promote artificial intelligence models for real-time Earth systems
• Includes a section on case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives

Table of contents

• Front Cover
• Intelligence Systems for Earth, Environmental and Planetary Sciences
• Copyright
• Dedication
• Contents
• Contributors
• Acknowledgments
• Chapter 1: Partial least squares regression to explore and predict environmental data
• Chapter 2: Study of solute dynamics in unsaturated sandy soil under controlled irrigation
• Chapter 3: Prediction of hydraulic heights water table for irrigation management in cranberry fields with Random Forest: ...
• Chapter 4: Spatial intelligence in AI applications for assessing soil health to monitor farming systems and associated ES ...
• Chapter 5: Drought forecasting based on machine learning techniques
• Chapter 6: How to use artificial intelligence to downscale climate change models data
• Chapter 7: Advanced methods of soil quality assessment for sustainable agriculture
• Chapter 8: Combining the RUSLE approach and GIS tools in soil water erosion monitoring and mapping (Northeastern Algeria)
• Chapter 9: Leveraging the use of mechanistic and machine learning models to assess interactions between ammonia concentra ...
• Chapter 10: Fallout radionuclide (137Cs) method for quantifying soil erosion rates in steep sloping hilly and mountainous ...
• Chapter 11: Coupling AquaCrop and machine learning approaches for cotton yield simulation
• Chapter 12: Attention-based Deep Neural Network for rainfall-runoff simulation across the continental United States
• Chapter 13: Digital soil mapping using geospatial data and machine learning techniques
• Chapter 14: Application of gene expression programming for prediction of dilution of inclined dense jet after the impact ...
• Chapter 15: Evolutionary prediction of geometrical and dilution characteristics of inclined dense jet over a sloped botto ...
• Chapter 16: Soil temperature prediction in ordinary and extremely hot weather using genetic programming
• Chapter 17: Feasibility of one-dimensional simulation of dam break via a novel finite volume scheme
• Author Index
• Index
• Back Cover