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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... predicting these systems is enormous. It requires identifying key linkages and feedback between them. A significant step in this direction has been a migration from a traditional laboratory approach to a natural laboratory approach. The ...
... predicting these systems is enormous. It requires identifying key linkages and feedback between them. A significant step in this direction has been a migration from a traditional laboratory approach to a natural laboratory approach. The ...
Page 2
... prediction studies. Encompassed in this challenge are the problems related to storage, representation, search, communication, visualization, and knowledge discovery. Limitations in any one of these phases results in only a subset of the ...
... prediction studies. Encompassed in this challenge are the problems related to storage, representation, search, communication, visualization, and knowledge discovery. Limitations in any one of these phases results in only a subset of the ...
Page 4
... . This technique is particularly useful when there is a large uncertainty with regards to the knowledge about the physical system, but there is a need for reliable prediction. Chapter 24 discusses Genetic 4 Hydroinformatics.
... . This technique is particularly useful when there is a large uncertainty with regards to the knowledge about the physical system, but there is a need for reliable prediction. Chapter 24 discusses Genetic 4 Hydroinformatics.
Page 5
... prediction. Chapter 24 discusses Genetic Algorithms, an optimization tool used in a wide variety of applications. In Chapter 25, we provide an introduction to Fuzzy Logic which moves us out of the probabilistic domain to enable us to ...
... prediction. Chapter 24 discusses Genetic Algorithms, an optimization tool used in a wide variety of applications. In Chapter 25, we provide an introduction to Fuzzy Logic which moves us out of the probabilistic domain to enable us to ...
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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