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- W2032749956 abstract "Complex decision-making problems are usually modeled in terms of a number of decisive variables that are related hierarchically. Pieces of evidence are aggregated in a bottom-up way to determine the final decision goal. For dealing with such problems, Ishizuka et al. [5,6] developed a rule-based inference procedure by using fuzzy sets to represent imprecise data, and employed the Dempster-Shafer theory to aggregate evidence for structural damage assessment. This paper highlights the necessity of applying the rules with all possible consequent clauses in the procedure with the considerations of information quality and quantity, when applying the procedure to more general decision-making problems. The use of such rules can provide high-quality information, which contains much less ignorance in the resultant information. Also, it can afford more information due to the decrease in total ignorance. A simple example with two cases is used to compare the results based on the two different presentations of rules in the inference procedure for illustrating the importance of considering the rules proposed in this paper." @default.
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- W2032749956 date "1997-11-01" @default.
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- W2032749956 title "An extended rule-based inference for general decision-making problems" @default.
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- W2032749956 doi "https://doi.org/10.1016/s0020-0255(96)00215-0" @default.
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