Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and ModelingModern hydrology is more interdisciplinary than ever. Staggering amounts and varieties of information pour in from GIS and remote sensing systems every day, and this information must be collected, interpreted, and shared efficiently. Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling introduces the tools, approache |
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Page ix
... extraction, feature selection, segmentation, classification, tracking, and statistical modeling from electro-optical, SAR, laser and hyperspectral datasets. Dr. Bajcsy's scientific interests include image and x Authors and Contributors ...
... extraction, feature selection, segmentation, classification, tracking, and statistical modeling from electro-optical, SAR, laser and hyperspectral datasets. Dr. Bajcsy's scientific interests include image and x Authors and Contributors ...
Page xi
... extract scientific information. Her research interests include: interannual climate and vegetation variability, global climate change, water, carbon, energy cycling, geomorphology, and information science. Taylor & Francis Taylor ...
... extract scientific information. Her research interests include: interannual climate and vegetation variability, global climate change, water, carbon, energy cycling, geomorphology, and information science. Taylor & Francis Taylor ...
Page xviii
... Extraction Peter Bajcsy 21 Feature Selection and Analysis Peter Bajcsy V 303 319 343 355 Soft Computing 379 381 22 Statistical Data Mining Amanda B. White and Praveen Kumar 409 23 Artificial Neural Networks Momcilo Markus 437 24 Genetic ...
... Extraction Peter Bajcsy 21 Feature Selection and Analysis Peter Bajcsy V 303 319 343 355 Soft Computing 379 381 22 Statistical Data Mining Amanda B. White and Praveen Kumar 409 23 Artificial Neural Networks Momcilo Markus 437 24 Genetic ...
Page 2
... extract higher level of information from it: information useful for a better understanding of the phenomena, as well as for socioeconomic benefits. As the volume and the dimensionality (number of variables) of the data grows, it is ...
... extract higher level of information from it: information useful for a better understanding of the phenomena, as well as for socioeconomic benefits. As the volume and the dimensionality (number of variables) of the data grows, it is ...
Page 4
... extraction; (6) feature selection; and (7) feature analysis and decision support. All eight chapters in Section IV ... extracting information from large multivariate datasets. Data mining technologies are becoming increasingly more ...
... extraction; (6) feature selection; and (7) feature analysis and decision support. All eight chapters in Section IV ... extracting information from large multivariate datasets. Data mining technologies are becoming increasingly more ...
Contents
7 | |
Managing and Accessing Large Datasets | 101 |
Data Communication | 161 |
Data Processing and Analysis | 257 |
Soft Computing | 379 |
Appendices | 477 |
Index | 529 |
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algorithm analysis application approach associated attributes bands boundary called Center chapter clusters complex component contains coordinate create data model data structures database datasets defined described distance distributed elements Engineering Equation error example extraction feature field Figure format function fuzzy geographic given grid HDF5 hydrologic illustrated implementation important input integration interface logical mean measurements metadata methods Modelshed multiple Name node objects operations optimization organized original output parameters perform prediction presented problem projection properties query raster records References relationship represent requires Research rules schema segment selection sensor shown simple sources spatial specific standard step storage stored structure transformation tree University values variables vector visualization xs:element