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Quantitative analysis of system coupling

Authors: Yin Zhang 0002; Hua Zhou; Qing Duan; Yun Liao; Junhui Liu; Zhenli He;

Quantitative analysis of system coupling

Abstract

To solve the problem that it is difficult to calculate system coupling in the field of systems science and software engineering, this article discussed quantitative analysis of system coupling. It is difficult to calculate system coupling in the field of system science and software engineering. Consequently, this paper discussed quantitative analysis of system coupling to solve this problem. According to the dependencies between the entities in a system, this paper proposed two mathematical models to measure system coupling based on entropy and judgment matrix. With these two models, it is possible to measure the coupling of each entity in the system and provide a basis for reducing the system coupling. Finally, this paper verified the validity and utility of the proposed models via a case of data warehouse structure.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Top 10%
Average
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