000			05675nam a22006015i 4500
001			978-3-540-28426-0
003			DE-He213
005			20161121230821.0
007			cr nn 008mamaa
008			100301s2006 gw | s |||| 0|eng d
020			_a9783540284260 _9978-3-540-28426-0
024	7		_a10.1007/3-540-28426-5 _2doi
050		4	_aGE45.M38
050		4	_aGE45.M37
072		7	_aRN _2bicssc
072		7	_aPBW _2bicssc
072		7	_aSCI026000 _2bisacsh
072		7	_aMAT003000 _2bisacsh
082	0	4	_a333.7 _223
245	1	0	_aEcological Informatics _h[electronic resource] : _bScope, Techniques and Applications / _cedited by Friedrich Recknagel.
250			_a2nd Edition.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2006.
300			_aXXXVI, 496 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aEcological Applications of Fuzzy Logic -- Ecological Applications of Qualitative Reasoning -- Ecological Applications of Non-supervised Artificial Neural Networks -- Ecological Applications of Genetic Algorithms -- Ecological Applications of Evolutionary Computation -- Ecological Applications of Adaptive Agents -- Bio-Inspired Design of Computer Hardware by Self-Replicating Cellular Automata -- Prediction and Elucidation of Stream Ecosystems -- Development and Application of Predictive River Ecosystem Models Based on Classification Trees and Artificial Neural Networks -- Modelling Ecological Interrelations in Running Water Ecosystems with Artificial Neural Networks -- Non-linear Approach to Grouping, Dynamics and Organizational Informatics of Benthic Macroinvertebrate Communities in Streams by Artificial Neural Networks -- Elucidation of Hypothetical Relationships between Habitat Conditions and Macroinvertebrate Assemblages in Freshwater Streams by Artificial Neural Networks -- Prediction and Elucidation of River Ecosystems -- Prediction and Elucidation of Population Dynamics of the Blue-green Algae Microcystis aeruginosa and the Diatom Stephanodiscus hantzschii in the Nakdong River-Reservoir System (South Korea) by a Recurrent Artificial Neural Network -- An Evaluation of Methods for the Selection of Inputs for an Artificial Neural Network Based River Model -- Utility of Sensitivity Analysis by Artificial Neural Network Models to Study Patterns of Endemic Fish Species -- Prediction and Elucidation of Lake and Marine Ecosystems -- A Comparison between Neural Network Based and Multiple Regression Models for Chlorophyll-a Estimation -- Artificial Neural Network Approach to Unravel and Forecast Algal Population Dynamics of Two Lakes Different in Morphometry and Eutrophication -- Hybrid Evolutionary Algorithm for Rule Set Discovery in Time-Series Data to Forecast and Explain Algal Population Dynamics in Two Lakes Different in Morphometry and Eutrophication -- Multivariate Time Series Prediction of Marine Zooplankton by Artificial Neural Networks -- Classification of Fish Stock-Recruitment Relationships in Different Environmental Regimes by Fuzzy Logic with Bootstrap Re-sampling Approach -- Computational Assemblage of Ordinary Differential Equations for Chlorophyll-a Using a Lake Process Equation Library and Measured Data of Lake Kasumigaura -- Classification of Ecological Images at Micro and Macro Scale -- Identification of Marine Microalgae by Neural Network Analysis of Simple Descriptors of Flow Cytometric Pulse Shapes -- Age Estimation of Fish Using a Probabilistic Neural Network -- Pattern Recognition and Classification of Remotely Sensed Images by Artificial Neural Networks.
520			_aEcological Informatics promotes interdisciplinary research between ecology and computer science on elucidation of principles of information processing in ecosystems, ecological sustainability by informed decision making, and bio-inspired computation. The 2nd edition of the book consolidates the scope, concepts, and techniques of this newly emerging discipline by a new preface and additional chapters on cellular automata, qualitative reasoning, hybrid evolutionary algorithms and artificial neural networks. It illustrates numerous applications of Ecological Informatics for aquatic and terrestrial ecosystems, image recognition at micro- and macro-scale as well as computer hardware design. Case studies focus on applications of artificial neural networks, evolutionary computation, cellular automata, adaptive agents, fuzzy logic as well as qualitative reasoning. The 2nd edition of the book includes an index with novel evolutionary algorithms for the discovery of multiple nonlinear functions and rule sets as well as parameter optimisation in complex ecological data.
650		0	_aEnvironment.
650		0	_aEarth sciences.
650		0	_aOceanography.
650		0	_aBioinformatics.
650		0	_aComputational biology.
650		0	_aEcology.
650		0	_aGeoecology.
650		0	_aEnvironmental geology.
650		0	_aEnvironmental sciences.
650	1	4	_aEnvironment.
650	2	4	_aMath. Appl. in Environmental Science.
650	2	4	_aEcology.
650	2	4	_aEarth Sciences, general.
650	2	4	_aOceanography.
650	2	4	_aComputer Appl. in Life Sciences.
650	2	4	_aGeoecology/Natural Processes.
700	1		_aRecknagel, Friedrich. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540283836
856	4	0	_uhttp://dx.doi.org/10.1007/3-540-28426-5
912			_aZDB-2-EES
950			_aEarth and Environmental Science (Springer-11646)
999			_c504426 _d504426