Programming Books C Java PHP Python Learn more Browse Programming Books
Trade in your item
Get a $3.56
Gift Card.
Have one to sell? Sell on Amazon
Flip to back Flip to front
Listen Playing... Paused   You're listening to a sample of the Audible audio edition.
Learn more
See this image

Artificial Intelligence Methods in the Environmental Sciences Paperback – December 12, 2008

ISBN-13: 978-1402091186 ISBN-10: 1402091184 Edition: 2009th

18 New from $70.98 7 Used from $70.98
Amazon Price New from Used from
Paperback
"Please retry"
$70.98 $70.98
Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student

NO_CONTENT_IN_FEATURE

Shop the new tech.book(store)
New! Introducing the tech.book(store), a hub for Software Developers and Architects, Networking Administrators, TPMs, and other technology professionals to find highly-rated and highly-relevant career resources. Shop books on programming and big data, or read this week's blog posts by authors and thought-leaders in the tech industry. > Shop now

Product Details

  • Paperback: 424 pages
  • Publisher: Springer; 2009 edition (December 12, 2008)
  • Language: English
  • ISBN-10: 1402091184
  • ISBN-13: 978-1402091186
  • Product Dimensions: 10.2 x 7.6 x 0.7 inches
  • Shipping Weight: 2.2 pounds
  • Amazon Best Sellers Rank: #6,306,334 in Books (See Top 100 in Books)

Editorial Reviews

From the Back Cover

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.

About the Author

Dr. Sue Ellen Haupt is Head of the Department of Atmospheric and Oceanic Physics at the Applied Research Laboratory of The Pennsylvania State University and Associate Professor of Meteorology. She received her Ph.D. in Atmospheric Science from the University of Michigan, M.S. in Mechanical Engineering from Worcester Polytechnic Institute and B.S. in Meteorology from Penn State. In addition to PSU, she has worked at New England Electric System, the National Center for Atmospheric Research, University of Colorado/Boulder, University of Nevada, Reno, and Utah State University. Her research emphasizes applying novel numerical techniques to environmental and fluid dynamics problems.

Dr. Antonello Pasini is a senior researcher at the Institute of Atmospheric Pollution of the National Research Council in Rome, Italy. He received his Italian Laurea in Physics from University of Bologna and specialized in atmospheric physics and meteorology at the Italian Met Service according to WMO criteria. He is an expert of complex systems and neural network modelling and applies his studies to several environmental problems, with a particular emphasis to climate change applications.

Dr. Caren Marzban is a senior physicist at the Applied Physics Laboratory, and an instructor at the Department of Statistics, University of Washington. He received his Ph.D. in theoretical physics from the University of North Carolina, at Chapel Hill. The early segment of his research career was in quantum gravity and string theory, but then he saw the light and began learning and applying statistics and machine learning techniques to any problem he can get his hands on.

Customer Reviews

There are no customer reviews yet.
5 star
4 star
3 star
2 star
1 star
Share your thoughts with other customers