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A new type of dyad fuzzy \(\beta \)-covering rough set models base on fuzzy information system and its practical application. (English) Zbl 07478935

Summary: In the era of big data, faced with massive and complex information, many mathematical concepts used to make judgments and decisions have emerged. In order to better integrate the multi-level fuzzy information, on the basis of the original covering rough set, we generalize the couple approximate operators defined by L.W. Ma to the information system and propose a new binary model – dyad fuzzy \(\beta \)-covering rough set models. This model can analyze and solve practical problems from multiple angles, so as to make more accurate decisions. In addition, in order to make the model more convenient for large and complex data processing, we use matrix to represent the model and realize it by computer programming. Finally, we illustrate the value of this model by solving a practical problem.

MSC:

68T37 Reasoning under uncertainty in the context of artificial intelligence
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