Download e-book for iPad: Analysis and Decision Making in Uncertain Systems by Professor Zdzislaw Bubnicki PhD (auth.)

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By Professor Zdzislaw Bubnicki PhD (auth.)

ISBN-10: 1447137604

ISBN-13: 9781447137603

ISBN-10: 1849969094

ISBN-13: 9781849969093

A unified and systematic description of research and selection difficulties inside of a large type of doubtful structures, defined through conventional mathematical equipment and via relational wisdom representations.

With specific emphasis on doubtful keep an eye on structures, Professor Bubnicki can provide a special method of formal types and layout (including stabilization) of doubtful platforms, according to doubtful variables and similar descriptions.

• advent and improvement of unique ideas of doubtful variables and a studying method inclusive of wisdom validation and updating.

• Examples in regards to the keep watch over of producing platforms, meeting tactics and job distributions in desktops point out the probabilities of useful purposes and ways to selection making in doubtful systems.

• contains certain difficulties akin to popularity and keep an eye on of operations below uncertainty.

• Self-contained.

If you have an interest in difficulties of doubtful keep watch over and choice help structures, this may be a invaluable addition for your bookshelf. Written for researchers and scholars within the box of keep an eye on and data technological know-how, this ebook also will profit designers of data and regulate systems.

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Additional info for Analysis and Decision Making in Uncertain Systems

Sample text

J = l,2, ... 4) The forms of KP presented above may be called non-parametric descriptions of the uncertain plant. Rk denotesan unknown vector parameter which is assumed to be a value of a random variable :X described by the probability density fx(x) (or by the respective form of the probability distribution in a discrete case). In this case KP = < for a functional plant and KP = for a relational plant. e. with parametric uncertainty described by probability distributions.

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. The setDu(z) of all possible decisions such that y e Dy for the plant described by R(u,y,z) has been introduced in Sect. 3 and has been called a relational knowledge of the decision making KD, or a relational decision algorithm.

In the non-parametric case, the plant is described by the given conditional probability distribution. g. [66, 73, 94]). In Sect. 1, a very short description of random variables is given to introduce the notation and to bring together formalisms concerning random, uncertain and fuzzy variables in a unified framework. 1 Random Variables and Probabilistic Forms of Knowledge Representations A random variable :X is defined by a set of variables X ~Rk (multidimensional vector space) and a probability distribution.

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


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