2009•Computer Engineering and ScienceRequires access

Uncertainty Measures of the Knowledge Based on Fuzzy Measuring in Incomplete Information Systems

Wenqi Liu

Abstract

Considering the impact of similar attributes and missing values in the incomplete information systems,it is unreasonable if you use the block size to measure the amount of information and the roughness of knowledge.This paper defines the information entropy of fuzzy measures,the rough entropy of knowledge and the rough set entropy,proves the rationality and its characteristics of the fuzzy measure rough entropy,and then takes an example to describe how to choose reasonable measurement to calculate the rough entroy,and applies it to the reduction of knowledge in incomplete information systems.

About this research paper

What this paper is about

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Rough set, Computer science, Entropy (arrow of time), Data mining, Fuzzy logic, Complete information, Fuzzy set, Measurement uncertainty