Entropy Theory and its Application in Environmental and Water Engineering (PDF)

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.