Sentence examples for granules of information from inspiring English sources

In this context, fuzzy sets represent linguistic granules of information, contained in the antecedents and consequents of the rules, whereas the data used in the genetic learning is assumed to be crisp.

Starting from the consideration that experts usually deal with imperfect spatial information through linguistic terms (e.g., they identify the approximate position of a phenomenon on a map and classify spatial properties through linguistic labels), this contribution proposes the use of linguistic granule of information to represent and manage imperfect spatial information.

For illustrative purposes, the study is focused on information granules formalized in terms of intervals (however the proposed approach becomes equally relevant for other formalism of information granules).

We show that the underlying arithmetic along with the concept of distance for this type of information granules can be expressed in a simple way, which facilitates the ensuing processing of information granules.

This study revisits generic concepts of information granules and Granular Computing in this setting and elaborates on a fundamental way of forming information granules (both sets – intervals as well as fuzzy sets) through applying a principle of justifiable granularity.

The design of information granules is central to the discipline of Granular Computing.

In this paper, we deal with a particular type of information granules, namely interval-valued data.

The characterization of information granules is offered in terms of measures of coverage, specificity, and entropy.

There is a remarkably rich landscape of fuzzy clustering and ensuing design procedures of information granules.

We discuss several main approaches to the design of information granules.

The study is devoted to the design of information granules of higher type (especially type-2) with the use of the principle of justifiable granularity.