Intelligence Systems for Earth, Environmental and Planetary Sciences Methods, Models and Applications

Langue : Anglais

Coordonnateurs : Bonakdari Hossein, Gumiere Silvio José

Couverture de l’ouvrage Intelligence Systems for Earth, Environmental and Planetary Sciences

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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 parts: Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets. Models, covering model development, data assimilation, and techniques in each field. Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental and planetary sciences problems, as well as future perspectives. This book will be of interest to students, academics and post-graduate 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.

1. Smart techniques for Earth, environmental and planetary sciences 2. Data preparation processes 3. Meta-heuristic algorithms for Earth, environmental and planetary sciences 4. Standard to Advanced version of meta-heuristic algorithms 5. The application of machine learning and evolutionary computational techniques 6. Case studies of applications of evolutionary computational techniques 7. Future applications

Dr. Bonakdari obtained his PhD in Civil Engineering from the University of Caen Normandy (France). He has worked for several organizations and most recently as an Associate Professor at the Department of Civil Engineering of the University of Ottawa (Canada). He is one of the most influential scientists in the field of developing novel algorithms for solving practical problems through the decision-making abilities of AI. His research also focuses on creating comprehensive methodologies in the areas of simulation modeling, optimization, and machine learning algorithms. The results obtained from his research have been published in international journals and presented at international conferences. He was included in the list of the world's top 2% scientists, published by Stanford University, and is on the Editorial board of several journals.
Silvio José Gumiere has been a professor in the Department of Soil Sciences at Laval University since 2011, after obtaining his Ph.D. in hydrological and erosion modelling from the GAIA doctoral School, Montpellier France. Since 2006 he has been working on various aspects of soil erosion, hydrology and soil physics as well as on the development of modelling tools for water and soil management in agricultural systems. He is an expert on the application of R-based numerical, statistical and geostatistical methods, such as time series analyses, image and signal processing, erosion modelling and spatial hydrology and spatial interpolation methods. His research has been published in over 50 papers in international journals with over 870 citations. He has also given ~70 presentations at national and international conferences. He is a Guest Editor for several special issues on hydrological modelling and machine learning techniques for solving applied science problems in hydrology, soil sciences, soil hydrology and environmental journals.

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