Journal ArticleDOI
ZSLF: A New Soft Likelihood Function Based on Z-Numbers and Its Application in Expert Decision System
TLDR
A Z-numbers soft likelihood function (ZSLF) decision model is proposed and the application examples show the rationality and effectiveness of the method and the advantages of the ZSLF decision model are shown.Abstract:
Due to the complexity of the real world, effective consideration of the ambiguity and reliability of information is a challenge that must be addressed by the correct decision of the expert system. Z-number provides us with a good idea because it describes the probability of the random variable and the possibility measure. Recently, Yager presented a soft likelihood function that effectively combines probabilistic evidence to deal with the conflict information. This article generalizes Yager's soft likelihood function based on Z-numbers and proposes a Z-numbers soft likelihood function (ZSLF) decision model. The application examples show the rationality and effectiveness of the method. The comparison and discussion further show the advantages of the ZSLF decision model.read more
Citations
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CaFtR: A Fuzzy Complex Event Processing Method
TL;DR: The proposed CaFtR method adequately makes use of network resources to achieve continuous and highly available complex event processing regardless of dynamic operator migrations under fuzzy environment.
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Probability transformation of mass function: A weighted network method based on the ordered visibility graph
TL;DR: Li et al. as discussed by the authors proposed a weighted network method based on the ordered visibility graph, named OVGWP, which considers not only the belief value itself, but also the cardinality of basic probability assignment.
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Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis
TL;DR: Wang et al. as mentioned in this paper introduced the concept of Belief Entropy-of-Entropy (BEoE), which expands entropy of entropy into belief structure and computes quadratic belief entropy to characterize the complexity of biological systems.
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A fuzzy preference-based Dempster-Shafer evidence theory for decision fusion
TL;DR: A novel BPA generation method for binary problems called as the base algorithm is designed based on the kernel density estimation to construct the probability density function models, using the pairwise learning method to establish binary classification pairs.
References
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TL;DR: A broad introduction into the topic of aggregation functions, and provides a concise account of the properties and the main classes of such functions, including classical means, medians, ordered weighted averaging functions, Choquet and Sugeno integrals, triangular norms, conorms and copulas, uninorms, nullnorms, and symmetric sums.
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Ronald R. Yager,Janusz Kacprzyk +1 more
TL;DR: This volume is the first in the literature on the increasingly popular Ordered Weighted Averaging (OWA) operators, making it possible to change the form of aggregation from the `pessimistic' minimum-type aggregation through all intermediate types, to the `optimistic' maximum-type aggregations.
Journal ArticleDOI
A Note on Z-numbers
TL;DR: The concept of a Z-number has a potential for many applications, especially in the realms of economics, decision analysis, risk assessment, prediction, anticipation and rule-based characterization of imprecise functions and relations.