Abstract
The key to granular computing is to make use of granules in problem solving. However, there are different granules at different levels of scale in data sets having hierarchical scale structures. And in real-world applications, there may exist multiple types of data in ordered information systems. Therefore, the concept of multi-scale ordered information systems is first introduced in this paper. The lower and upper approximations in multi-scale ordered information systems are then defined, and their properties are examined.
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Gu, SM., Wu, Y., Wu, WZ., Li, TJ. (2014). Knowledge Approximations in Multi-scale Ordered Information Systems. In: Miao, D., Pedrycz, W., Ślȩzak, D., Peters, G., Hu, Q., Wang, R. (eds) Rough Sets and Knowledge Technology. RSKT 2014. Lecture Notes in Computer Science(), vol 8818. Springer, Cham. https://doi.org/10.1007/978-3-319-11740-9_48
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DOI: https://doi.org/10.1007/978-3-319-11740-9_48
Publisher Name: Springer, Cham
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