A Similarity Between Uncertain Data Measurement Method Based on stochastic simulation

Cheng, Yuan and Chi, Ronghua and Lang, Dapeng (2020) A Similarity Between Uncertain Data Measurement Method Based on stochastic simulation. In: Mobimedia 2020, 27-28 August 2020, Cyberspace.

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Abstract

The distance measurement between uncertain data is an important basis for accurate clustering. Taking full advantage of the uncertainty characteristics of the object will help to represent the uncertain data more accurately and calculate its distance. Based on the probability distribution function to represent the characteristics of uncertainty distribution, this paper studies a method for measuring distance between uncertain objects based on stochastic simulation. The effectiveness of the proposed method is verified by experiments.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: uncertain data distance measurement probability density function stochastic simulation
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor I.
Date Deposited: 04 Feb 2021 14:21
Last Modified: 04 Feb 2021 14:21
URI: https://eprints.eudl.eu/id/eprint/872

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