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Large group decision-making based on interval rough integrated cloud model
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DOI：10.1016/j.aei.2023.101964.png)
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Since different uncertainties exist in the large group decision-making (LGDM) process, such as randomness, diversity and fuzziness, a single method may be insufficient to address LGDM. Hence, this paper proposes a hybrid model that a new similarity calculation method for cloud model, the netting clustering and interval rough integrated cloud (IRIC) are combined to solve LGDM in uncertain linguistic environment. First, a new similarity method for cloud model is presented, based on which a netting clustering method is provided. The similarity calculation method has higher differentiation degree and has overcome some shortcomings of previous ones. Second, two hybrid-weighting methods are utilized respectively to calculate expert weights and attribute weights for making the decision-making process more credible and scientific. Finally, the IRIC method is applied to LGDM for dealing with the randomness and uncertainty. In addition, an example is offered to demonstrate the application of the proposed approach. According to a time-consuming test, the proposed method is more suitable to address LGDM in the big data environment.
Keyword:
Large group decision-making
Interval rough integrated cloud
Similarity
Cluster analysis
Hybrid weights
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