Research Article
A Similarity Between Uncertain Data Measurement Method Based on stochastic simulation
@INPROCEEDINGS{10.4108/eai.27-8-2020.2296730, author={Yuan Cheng and Ronghua Chi and Dapeng Lang}, title={A Similarity Between Uncertain Data Measurement Method Based on stochastic simulation}, proceedings={Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2020}, month={11}, keywords={uncertain data distance measurement probability density function stochastic simulation}, doi={10.4108/eai.27-8-2020.2296730} }- Yuan Cheng
Ronghua Chi
Dapeng Lang
Year: 2020
A Similarity Between Uncertain Data Measurement Method Based on stochastic simulation
MOBIMEDIA
EAI
DOI: 10.4108/eai.27-8-2020.2296730
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.
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