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The evidential reasoning approach for multiple attribute decision analysis using intuitionistic fuzzy information

机译:基于直觉模糊信息的多属性决策分析的证据推理方法

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The evidential reasoning (ER) approach is a method for multiple attribute decision analysis (MADA) under uncertainties. It improves the insightfulness and rationality of a decision making process by using a belief decision matrix (BDM) for problem modelling and the Dempster-Shafer (D-S) theory of evidence for attribute aggregation. While in reality, several types of uncertainties such as fuzziness may be provided. So in this paper, one of the types-intuitionistic fuzzy number will be investigated. The provided assessment information will be given using intutionistic fuzzy information. First, the evidential reasoning approach and the intuitionistic fuzzy information will be introduced. Then, the intuitionistic fuzzy information will be incorporated into the ER theory and the process will also be provided. At the end, a numerical example is examined.
机译:证据推理(ER)方法是不确定性下的多属性决策分析(MADA)方法。通过使用信念决策矩阵(BDM)进行问题建模和使用证据的Dempster-Shafer(D-S)证据理论进行属性聚合,可以提高决策过程的洞察力和合理性。实际上,可以提供几种类型的不确定性,例如模糊性。因此,本文将研究一种类型直觉模糊数。所提供的评估信息将使用直觉模糊信息给出。首先,将介绍证据推理方法和直觉模糊信息。然后,将直觉的模糊信息纳入ER理论中,并提供该过程。最后,研究了一个数值示例。

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