Title :
Integration of Multiple Qualitative Probabilistic Networks based on probabilistic rough sets
Author :
Lv, Yali ; Liao, Shizhong
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
Abstract :
The problem of integrating multiple-source uncertain information is crucial in many applications. In this paper, we propose an integration method of multiple Qualitative Probabilistic Networks (QPNs). Assuming that each QPN has the same nodes, we integrate the qualitative signs and structure of multiple QPNs based on probabilistic rough sets. Specifically, we first take the probabilistic-rough-set-based dependency degree as the strength of qualitative influences to reduce ambiguities that arise from the qualitative signs integration. Secondly, we give the definition of the whole influence strength, and then discuss two cases to delete the cycles in the process of structure integration. Finally, we verify the correctness of the integration method by the simulation experiments.
Keywords :
common-sense reasoning; inference mechanisms; knowledge representation; rough set theory; multiple qualitative probabilistic network; multiple source uncertain information; probabilistic rough set; qualitative sign integration; structure integration; RNA;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622708