Download Analysis and Decision Making in Uncertain Systems by Professor Zdzislaw Bubnicki PhD (auth.) PDF

By Professor Zdzislaw Bubnicki PhD (auth.)

A unified and systematic description of study and determination difficulties inside a large category of doubtful platforms, defined by means of conventional mathematical equipment and by way of relational wisdom representations.

With specified emphasis on doubtful regulate platforms, Professor Bubnicki supplies a different method of formal types and layout (including stabilization) of doubtful platforms, in accordance with doubtful variables and similar descriptions.

• advent and improvement of unique techniques of doubtful variables and a studying strategy which includes wisdom validation and updating.

• Examples about the regulate of producing platforms, meeting techniques and activity distributions in computers point out the probabilities of useful functions and ways to selection making in doubtful systems.

• comprises particular difficulties akin to popularity and keep watch over of operations lower than uncertainty.

• Self-contained.

If you have an interest in difficulties of doubtful keep watch over and determination aid structures, this may be a helpful addition on your bookshelf. Written for researchers and scholars within the box of keep watch over and knowledge technology, this booklet also will profit designers of data and keep an eye on systems.

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P(z). P(z). For the given desirable value y * we can consider two cases: in the first case the deterministic decision algorithm IJ'(z) is obtained via determinization of the knowledge of the plant KP, and in the second case the deterministic decision algorithm IJ'd(z) is based on the determinization of the knowledge of the decision making KD obtained from KP for the given y • . In the first case we determine the mean value y(z) = Jydy . 18). 23) has a unique solution. e. the set of all pairs (u,z) for which it is possible that y = y*.

22) gives y =~cu + z =$(u,z). From the equation $(u,z) = y * we obtain the decision algorithm 2(y • -c) u = 'P(z) = - - ' - - - 3z 24 Analysis and Decision Making in Uncertain Systems z z -----;;. 6. 7. 5 Discrete Case Assume that Now the relation R (u, y) is a set of pairs Ciij, Y;) selected from U x Y, and may be described by the zero-one matrix Xji = { 1 if (iij,Y;)ER 0 if (iij,Y;)~R. j=l, ... ,a, i=l, ... ,p. The setsDu c U and Dy c Y may be determined by the sets of the respective indexes /', J c {1,2, ...

P(z). For the given desirable value y * we can consider two cases: in the first case the deterministic decision algorithm IJ'(z) is obtained via determinization of the knowledge of the plant KP, and in the second case the deterministic decision algorithm IJ'd(z) is based on the determinization of the knowledge of the decision making KD obtained from KP for the given y • . In the first case we determine the mean value y(z) = Jydy . 18). 23) has a unique solution. e. the set of all pairs (u,z) for which it is possible that y = y*.

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