Book description
Entropy Theory and its Application in Environmental and Water
Engineering responds to the need for a book that deals with
basic concepts of entropy theory from a hydrologic and water
engineering perspective and then for a book that deals with
applications of these concepts to a range of water engineering
problems. The range of applications of entropy is constantly expanding
and new areas finding a use for the theory are continually emerging.
The applications of concepts and techniques vary across different
subject areas and this book aims to relate them directly to practical
problems of environmental and water engineering.
The book presents and explains the Principle of Maximum Entropy
(POME) and the Principle of Minimum Cross Entropy (POMCE) and their
applications to different types of probability distributions. Spatial
and inverse spatial entropy are important for urban planning and are
presented with clarity. Maximum entropy spectral analysis and minimum
cross entropy spectral analysis are powerful techniques for addressing
a variety of problems faced by environmental and water scientists and
engineers and are described here with illustrative examples.
Giving a thorough introduction to the use of entropy to measure the
unpredictability in environmental and water systems this book will add
an essential statistical method to the toolkit of postgraduates,
researchers and academic hydrologists, water resource managers,
environmental scientists and engineers. It will also offer a valuable
resource for professionals in the same areas, governmental
organizations, private companies as well as students in earth
sciences, civil and agricultural engineering, and agricultural and
rangeland sciences.
This book:
- Provides a thorough introduction to entropy for beginners and more
experienced users
- Uses numerous examples to illustrate the applications of the
theoretical principles
- Allows the reader to apply entropy theory to the solution of
practical problems
- Assumes minimal existing mathematical knowledge
- Discusses the theory and its various aspects in both univariate
and bivariate cases
- Covers newly expanding areas including neural networks from an
entropy perspective and future developments.
Vijay P. Singh, Texas A & M University, USA
