ENTROPIA INFORMACYJNA PDF

Akizilkree entropia — English translation — Linguee Qualitative modelling of dynamical systems. The S econd Law of Thermodynamics is relentless. Examples of use in the Polish literature, quotes and news about morejna. This book is your ultimate resource for Morena Baccarin.

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The multi-valued diagnostic model has been assumed. Proposed measures can be used in the manner similar to Shannon entropy use for the diagnostic model analysis and the diagnostic algorithm planning process. Introduction Optimal set of diagnostic symptoms determination is one of the most important problems.

Applied optimization method depends on the form of diagnostic model. Recently, more attention is paid to the qualitative approximate, multi-valued models [2, 5, 6, 7].

One of the way of solving diagnostic algorithm determination problem consists in applying the information-based analysis [2, 8], i. This aim can be reached with the Shannon- introduced quantities: the entropy, and the amount of information [9]. In this paper the combinatorial diagnostic entropy denoted with H Bc.

The set of desirable properties of proposed measure will be determined taking the diagnostics point of view into account. Assumptions 1. For all the symptoms the following holds: - The multi-valued diagnostic model has been presented in the form of a diagnostic matrix G.

The combinatorial diagnostic entropy The form of the function f n can be defined with two methods: a formal deduction, b arbitrary acceptance of a certain form of the function and proving that it shows the postulated properties. Further considerations will be based on the following theorem proved in [2]: - On the grounds of relationships 17 and 18 , the notion of the symptom combinatorial informativity can be defined.

Definition The symptom d r combinatorial informativity is equal to the difference in the condition uncertainty before this symptom has been selected and the uncertainty remaining after the selection. Conclusion What has been shown in the paper is that the system condition uncertainty can be described with functions of the non-logarithmic form. A new, non- logarithmic combinatorial diagnostic entropy has been introduced.

It describes the number of fault pairs which have to be distinguished during diagnosing process. Treating the assumed combinatorial diagnostic entropy - In this way relationships have been derived that facilitate explicit, quantitative assessment of the informativity of a single symptom as well as that of a symptoms set.

It has been proved that the informativity J Bc dr shows the property of additivity. References 1. Behara M.

Borowczyk H. Rozprawa doktorska. WAT, Warszawa, 3. Theory, Stat. Functions and Random Processes, 4. Havrda M. Kybernetica, 3 , Iserman R. Korbicz J. Models, Artificial intelligence, Applications. Springer- Verlag, 7. Lunze J. Motivation, methods, and prospective applications. Rosenhaus M. Shannon C. The Bell Technical Journal, Vol.

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