Probabilistic Model of Canonically Conjugated Fuzzy Subsets
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Data in informatics is the set of information units. Each information unit can be presented as four: (object, sign, value, plausibility). Inaccuracy belongs to information content ( component "value"), and uncertainty - to its verity (component "plausibility"). For the given various information there exists the contradiction between inaccuracy of expression content and its uncertainty: with the increase of expression accuracy, its uncertainty rises as well and vice versa, uncertain character of information leads to some inaccuracy of the final conclusions, received from this information. We se...
Data in informatics is the set of information units. Each information unit can be presented as four: (object, sign, value, plausibility). Inaccuracy belongs to information content ( component "value"), and uncertainty - to its verity (component "plausibility"). For the given various information there exists the contradiction between inaccuracy of expression content and its uncertainty: with the increase of expression accuracy, its uncertainty rises as well and vice versa, uncertain character of information leads to some inaccuracy of the final conclusions, received from this information. We see that from one side these notions are in contradiction in a certain way, and from another side - complete each other upon the data presentation. Generally, fuzzy subset is constructed on the basis of expert estimation of one of these commutating components. Constructed in this way, Fuzzy subset incompletely characterizes the informational unit. We offer the method of construction of the informational unit membership function taking into account both canonically conjugated components simultaneously and hence describing this unit in most complete and optimal way.
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