Sentence examples for and vagueness of data in the from inspiring English sources

The phrase "and vagueness of data in the" is grammatically correct but incomplete, making it less usable in written English without additional context.
You can use it when discussing issues related to unclear or imprecise data in a specific context, such as research or data analysis.
Example: "The report highlighted the challenges posed by the vagueness of data in the study, making it difficult to draw definitive conclusions."
Alternatives: "ambiguity of data in the" or "uncertainty of data in the".

Exact(1)

In this method, to deal with uncertainty and vagueness of data in the primary phases of product design, performance of design concepts with respect to quantitative and qualitative criteria are concurrently evaluated using rough set and fuzzy set.

Similar(59)

Using fuzzy numbers is a powerful tool to overcome the uncertainty and vagueness of data.

The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods.

Pompeo, speaking to journalists traveling with him in Seoul, defended the lack of details and vagueness of the document.

Due to vagueness of the decision data, the crisp data are inadequate for real-life situations.

However, there is uncertainty and vagueness existing in the judgment of students' need and expectations.

A recent case involving the vagueness of language in the CFAA is United States v. Nosal, 642 F.3d 781 (9th Cir. 2011).

In order to deal with vagueness of the data Fuzzy Set Theory (FST) and possibility approach are used to overcome the disadvantages of the conventional probability based approaches.

Fuzzy logic combined with expert elicitation is employed in order to deal with vagueness of the data, to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing.

In this regard, new developments of the model are required based on fuzzy, interval, green, or other uncertain numbers dependent of the type of vagueness of the data.

Explicitly, new development are expected to provide ways of filling in missing data and addressing data uncertainty and vagueness using dynamic models of the very systems that these data pertains to.

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