Artificial Intelligence Methods in the Environmental Sciences

• Corporate Author: SpringerLink (Online service)
• Other Authors: Haupt, Sue Ellen. (Editor), Pasini, Antonello. (Editor), Marzban, Caren. (Editor)
• Format: Electronic
• Language: English
• Published: Dordrecht : Springer Netherlands, 2009.
• Subjects: Environmental sciences.; Geography.; Mathematical geography.; Artificial intelligence.; Physics.; Environment.; Environment, general.; Artificial Intelligence (incl. Robotics).; Math. Appl. in Environmental Science.; Numerical and Computational Methods.; Computer Applications in Earth Sciences.; Earth Sciences, general.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4020-9119-3

 How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence techniques, including: -neural networks -decision trees -genetic algorithms -fuzzy logic Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. The book is a scientific as well as a cultural blend: one culture entwines ideas with a thread, while another links them with a red line. Thus, a red thread ties the book together and weaves the fabric of the methods into a tapestry that pictures the natural data-driven artificial intelligence methods in the light of the more traditional modeling techniques. The international authors, who are recognized major experts in their respective fields, bring to life ways to apply artificial intelligence to problems in the environmental sciences, demonstrating the power of these data-based methods.