Computational Intelligence Techniques in Earth and Environmental Sciences - Info and Reading Options
By Tanvir Islam, Prashant K. Srivastava, Manika Gupta, Xuan Zhu and Saumitra Mukherjee

"Computational Intelligence Techniques in Earth and Environmental Sciences" is published by Springer in Feb 15, 2014 and it has 266 pages.
“Computational Intelligence Techniques in Earth and Environmental Sciences” Metadata:
- Title: ➤ Computational Intelligence Techniques in Earth and Environmental Sciences
- Authors: Tanvir IslamPrashant K. SrivastavaManika GuptaXuan ZhuSaumitra Mukherjee
- Number of Pages: 266
- Publisher: Springer
- Publish Date: Feb 15, 2014
“Computational Intelligence Techniques in Earth and Environmental Sciences” Subjects and Themes:
- Subjects: ➤ Earth sciences - Computational intelligence - Data processing - Environmental sciences - Earth sciences, data processing - Climatic changes - Euthenics - Nature and nurture - Adaptation (Biology) - Ecology - Environment, general - Earth System Sciences
Edition Specifications:
- Format: hardcover
Edition Identifiers:
- The Open Library ID: OL28020874M - OL20720685W
- Library of Congress Control Number (LCCN): 2014931489
- ISBN-13: 9789401786416
- ISBN-10: 9401786410
- All ISBNs: 9401786410 - 9789401786416
AI-generated Review of “Computational Intelligence Techniques in Earth and Environmental Sciences”:
"Computational Intelligence Techniques in Earth and Environmental Sciences" Description:
The Open Library:
Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered are divided into three categories - classical intelligence techniques, probabilistic and transforms intelligence techniques, and hybrid intelligence techniques. Further topics given treatment in this volume include meteorology, atmospheric modeling, climate change, water resources engineering, and hydrological modeling. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists, and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.
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