Hydrozip: how hydrological knowledge can be used to improve compression of hydrological data

DOI10.3390/E15041289zbMath1302.86030OpenAlexW2131279443WikidataQ61938856 ScholiaQ61938856MaRDI QIDQ742695

Nick van de Giesen, Marc B. Parlange, Steven V. Weijs

Publication date: 19 September 2014

Published in: Entropy (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3390/e15041289

zbMATH Keywords

algorithmic information theorydata compressioninferencehydrologystreamflowMOPEX

Mathematics Subject Classification ID

Geostatistics (86A32) Computational methods for problems pertaining to geophysics (86-08) Information theory (general) (94A15) Statistical aspects of information-theoretic topics (62B10) Channel models (including quantum) in information and communication theory (94A40)

Uses Software

• HydroZIP

Cites Work

• A Mathematical Theory of Communication
• A philosophical treatise of universal induction
• Expanding the algorithmic information theory frame for applications to Earth observation
• On universal prediction and Bayesian confirmation
• Application of Kolmogorov complexity and universal codes to identity testing and nonparametric testing of serial independence for time series
• Clustering by Compression
• A Theory of Program Size Formally Identical to Information Theory
• A universal algorithm for sequential data compression
• Arithmetic Coding
• A Method for the Construction of Minimum-Redundancy Codes
• On the Length of Programs for Computing Finite Binary Sequences
• Three approaches to the quantitative definition of information^*
• A formal theory of inductive inference. Part I
• A new look at the statistical model identification

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