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Artificial neural networks in biological and environmental analysis

Record Type:	Electronic resources : monographic
Author:	HanrahanGrady,
Place of Publication:	Boca Raton, FL
Published:	CRC Press;
Year of Publication:	c2011
Description:	1 online resource (xxii, 188 p.)ill. (some col.) :
Series:	Analytical chemistry series
Subject:	Artificial intelligence - Biological applications -
Subject:	Biology - Data processing -
Subject:	Environmental engineering - Data processing -
Subject:	Neural networks (Computer science) - Scientific applications -
Subject:	Electronic books -
Online resource:	http://www.crcnetbase.com/isbn/978-1-4398-1258-7
Notes:	Description based on print version record
Summary:	"Drawing on the experience and knowledge of a practicing professional, this book provides a comprehensive introduction and practical guide to the development, optimization, and application of artificial neural networks (ANNs) in modern environmental and biological analysis. Based on our knowledge of the functioning human brain, ANNs serve as a modern paradigm for computing. Presenting basic principles of ANNs together with simulated biological and environmental data sets and real applications in the field, this volume helps scientists comprehend the power of the ANN model to explain physical concepts and demonstrate complex natural processes"--Provided by publisher
ISBN:	9781439812594electronic bk.
ISBN:	1439812594electronic bk.
ISBN:	hbk.
ISBN:	hbk.

Artificial neural networks in biological and environmental analysis
Hanrahan, Grady

Artificial neural networks in biological and environmental analysis / Grady Hanrahan - Boca Raton, FL : CRC Press, c2011. - 1 online resource (xxii, 188 p.) ; ill. (some col.). - (Analytical chemistry series).
Description based on print version record.
Includes bibliographical references and index.
ISBN 9781439812594ISBN 1439812594
Artificial intelligenceBiologyEnvironmental engineeringNeural networks (Computer science)Electronic books -- Biological applications -- Data processing -- Data processing -- Scientific applications

Artificial neural networks in biological and environmental analysis
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330 $a "Drawing on the experience and knowledge of a practicing professional, this book provides a comprehensive introduction and practical guide to the development, optimization, and application of artificial neural networks (ANNs) in modern environmental and biological analysis. Based on our knowledge of the functioning human brain, ANNs serve as a modern paradigm for computing. Presenting basic principles of ANNs together with simulated biological and environmental data sets and real applications in the field, this volume helps scientists comprehend the power of the ANN model to explain physical concepts and demonstrate complex natural processes"--Provided by publisher
330 $a "The cornerstones of research into prospective tools of artificial intelligence originate from knowledge of the functioning brain. Like most transforming scientific endeavors, this field-- once viewed with speculation and doubt--has had profound impacts in helping investigators elucidate complex biological, chemical, and environmental processes. Such efforts have been catalyzed by the upsurge in computational power and availability, with the co-evolution of software, algorithms, and methodologies contributing significantly to this momentum. Whether or not the computational power of such techniques is sufficient for the design and construction of truly intelligent neural systems is of continued debate. In writing Artificial Neural Networks in Biological and Environmental Analysis, my aim was to provide in-depth and timely perspectives on the fundamental, technological, and applied aspects of computational neural networks. By presenting basic principles of neural networks together with real applications in the field, I seek to stimulate communication and partnership among scientists in the fields as diverse as biology, chemistry, mathematics, medicine, and environmental science. This interdisciplinary discourse is essential not only for the success of independent and collaborative research and teaching programs, but also for the continued acquiescence of the use of neural network tools in scientific inquiry"--Provided by publisher
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