Read e-book online Analysis and Decision Making in Uncertain Systems PDF

By Professor Zdzislaw Bubnicki PhD (auth.)

ISBN-10: 1447137604

ISBN-13: 9781447137603

ISBN-10: 1849969094

ISBN-13: 9781849969093

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

With unique emphasis on doubtful regulate structures, Professor Bubnicki supplies a different method of formal versions and layout (including stabilization) of doubtful platforms, according to doubtful variables and comparable descriptions.

• creation and improvement of unique options of doubtful variables and a studying method such as wisdom validation and updating.

• Examples about the keep an eye on of producing structures, meeting approaches and job distributions in computers point out the chances of functional functions and ways to determination making in doubtful systems.

• contains specific difficulties similar to reputation and regulate of operations less than uncertainty.

• Self-contained.

If you have an interest in difficulties of doubtful keep an eye on and determination help platforms, this can be a necessary addition for your bookshelf. Written for researchers and scholars within the box of keep watch over and knowledge technological know-how, this booklet also will profit designers of data and keep watch over systems.

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Additional info for Analysis and Decision Making in Uncertain Systems

Sample text

Fi (y)=--exp(--). 32 4~ y Then E Y (y) = 0 and the variance 2 ay 16 =? 45) . e. one of the possible descriptions of the random decision algorithm. 8 Non-parametric Uncertainty. Discrete Case In the discrete case u E U = {iii, liz, ... Yz, ... Yp}, Let us start with a plant without disturbances, described by KP in the form of a matrix of conditional probabilities (see Sect. 1) py =[pij]i=l,2, ... ,p j = l,2, ...

Jz i'. ;;. 4. 3. Let us determine the optimal decision u * for one-dimensional plant and the following data: Ae-Ax fx(x) = { 0 for x;:::: 0 for x ~ 0. In this case, the set Dx(Dy,u) is determined by the inequality l2_ < < Y2 . _1_). u 2u Y! u 48 Analysis and Decision Making in Uncertain Systems . dp(u) . 33) may be considered as a result of the determinization of the relational and random plant under consideration. For the fixed x and z we can determine the largest set Du(z;x) c U such that the implication u e Du(z;x) ~ y e Dy is satisfied.

Version II. Y;u,z) = Jy fy(y;u,z)dy y ~

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


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