Abstract
In many fields of research where different gridded spatial data needs to be processed, the grids do not align properly. This can be for a multitude of reasons, and it complicates drawing conclusions and further processing the data; it requires one grid to be transformed to match the other grid. In this article, we present the first results of a completely new approach to transforming data that are represented in one grid, to have it match a given target grid. The approach uses techniques from artificial intelligence and simulates an intelligent reasoning on how the grid can be transformed, using additionally available information to estimate the underlying distribution. The article describes the algorithm, and results on artificial datasets are discussed.
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Verstraete, J. (2014). A Fuzzy Rulebase Approach to Remap Gridded Spatial Data: Initial Observations. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_38
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DOI: https://doi.org/10.1007/978-3-319-08795-5_38
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08794-8
Online ISBN: 978-3-319-08795-5
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