Abstract
The Dempster–Shafer theory of evidence for attribute aggregation provides a method to deal with uncertainty reasoning. In this paper, uncertainty reasoning method based on rule-base with certainty interval is investigated. First, knowledge representation with interval uncertainty is defined and the matching principle is given. Then, a rule-based inference method under interval numbers using Dempster–Shafer theory is derived. A numerical example is examined to show the implementation process of the proposed method.
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Acknowledgment
This work is supported by the National Science Foundation of China (Grant No. 61175055), Sichuan Key Technology Research and Development Program (Grant No. 2011FZ0051), Radio Administration Bureau of MIIT of China (Grant No. [2011] 146), China Institution of Communications (Grant No. [2011] 051).
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Jin, L., Xu, Y. (2014). A Rule-Based Inference Method Using Dempster–Shafer Theory. In: Wen, Z., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent Systems and Computing, vol 278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54930-4_7
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DOI: https://doi.org/10.1007/978-3-642-54930-4_7
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