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Titlebook: Entropy and Energy Dissipation in Water Resources; V. P. Singh,M. Fiorentino Book 1992 Springer Science+Business Media Dordrecht 1992 agri

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Urban Development as a Process,’ maximum entropy principle (MaxEnt), Kullback’s minimum cross-entropy principle (MinxEnt), generalised maximum entropy and minimum cross-entropy principles, inverse entropy optimization principles, minimum interdependence principle, minimax entropy principle and finally, the dual entropy optimizati
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https://doi.org/10.1057/9780230119581 one group of applications basically rely on the concept of “thermodynamic entropy”, where problems associated with river morphology and river hydraulics are handled by a rather non-probabilistic approach. The second group of studies use the concept of “informational entropy” within a probabilistic
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Daniela Zamfir,Ilinca-Valentina Stoicaine the concept of “entropy” as function of the knowledge, and to derive some simple reference ideas in order to analyze the general problem of the hydrological knowledge..First, the general problem of space and time resolution in hydrological data is introduced, starting from known problems and the
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The Theory of City Size and Spacing, the streamflow records, is the existence of intermittent missing data gaps. This paper addresses this issue and proposes data infilling procedures based on pattern recognition techniques. The characteristics and relationships of distinct groups of data, rather than the entire time series as a whole
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https://doi.org/10.1057/9781403981875m (HFS) and its unavailability. Historical data on failures of operational HFSs provided information on the expected failure rates and the out-of-service time contributors of the most common HFS equipment. A dynamic event tree methodology was employed for a probabilistic analysis of the HFS. A compu
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