This paper 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, forms the basis of model development. Two types of models are proposed, including the models for infilling missing values based on the characteristics and relationships of only the streamflow time series with missing data values; and the models which also incorporate relevant information on the characteristics and relationships of the other time series of nearby rivers. The latter type of model are found to perform better. -from Author
CITATION STYLE
Panu, U. S. (1992). Application of some entropic measures in hydrologic data infilling procedures. Entropy and Energy Dissipation in Water Resources, 175–192. https://doi.org/10.1007/978-94-011-2430-0_9
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