QOS of Data Networks Analyzing Based on the Fuzzy Knowledge Base

Author(s):  
L. Globa ◽  
Z. Savchuk ◽  
O. Vasylenko ◽  
E. Siemens
2018 ◽  
Vol 8 (6) ◽  
pp. 864 ◽  
Author(s):  
Murat Luy ◽  
Volkan Ates ◽  
Necaattin Barisci ◽  
Huseyin Polat ◽  
Ertugrul Cam

Big Data ◽  
2016 ◽  
pp. 711-733 ◽  
Author(s):  
Jafreezal Jaafar ◽  
Kamaluddeen Usman Danyaro ◽  
M. S. Liew

This chapter discusses about the veracity of data. The veracity issue is the challenge of imprecision in big data due to influx of data from diverse sources. To overcome this problem, this chapter proposes a fuzzy knowledge-based framework that will enhance the accessibility of Web data and solve the inconsistency in data model. D2RQ, protégé, and fuzzy Web Ontology Language applications were used for configuration and performance. The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. The result shows that the D2RQ is more scalable with respect to performance comparison. Finally, the conclusion and future lines of the research were provided.


1998 ◽  
Vol 98 (3) ◽  
pp. 267-278 ◽  
Author(s):  
John Dewey Jones ◽  
Yao Hua

Wear ◽  
1992 ◽  
Vol 156 (2) ◽  
pp. 239-250 ◽  
Author(s):  
K. Stupka ◽  
M. Dohnal

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