Temat: estimators - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Monitoring of chlorine concentration in drinking water distribution systems using an interval estimator
Autorzy:: Łangowski, R.
Brdyś, M. A.
Powiązania:: https://bibliotekanauki.pl/articles/929615.pdf
Data publikacji:: 2007
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: estymator
jakość wody
metoda ograniczająca
modelowanie dynamiczne
estimators
bounding methods
modelling dynamics
water quality
Opis:: This paper describes the design of an interval observer for the estimation of unmeasured quality state variables in drinking water distribution systems. The estimator utilizes a set bounded model of uncertainty to produce robust interval bounds on the estimated state variables of the water quality. The bounds are generated by solving two differential equations. Hence the numerical efficiency is sufficient for on-line monitoring of the water quality. The observer is applied to an exemplary water network and its performance is validated by simulations.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2007, 17, 2; 199-216
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: A complete gradient clustering algorithm formed with kernel estimators
Autorzy:: Kulczycki, P.
Charytanowicz, M.
Powiązania:: https://bibliotekanauki.pl/articles/907781.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: analiza danych
eksploracja danych
grupowanie
metoda statystyczna
estymacja jądrowa
obliczenia numeryczne
data analysis
data mining
clustering
gradient procedures
nonparametric statistical methods
kernel estimators
numerical calculations
Opis:: The aim of this paper is to provide a gradient clustering algorithm in its complete form, suitable for direct use without requiring a deeper statistical knowledge. The values of all parameters are effectively calculated using optimizing procedures. Moreover, an illustrative analysis of the meaning of particular parameters is shown, followed by the effects resulting from possible modifications with respect to their primarily assigned optimal values. The proposed algorithm does not demand strict assumptions regarding the desired number of clusters, which allows the obtained number to be better suited to a real data structure. Moreover, a feature specific to it is the possibility to influence the proportion between the number of clusters in areas where data elements are dense as opposed to their sparse regions. Finally, the algorithm-by the detection of one-element clusters-allows identifying atypical elements, which enables their elimination or possible designation to bigger clusters, thus increasing the homogeneity of the data set.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2010, 20, 1; 123-134
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Bayes sharpening of imprecise information
Autorzy:: Kulczycki, B.
Charytanowicz, M.
Powiązania:: https://bibliotekanauki.pl/articles/908526.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: informacja niepewna
współczynnik kondycji
estymator jądrowy
funkcja strat
obliczenia numerycze
imprecise information
sharpening
conditioning factors
kernel estimators
Bayes decision rule
nonsymmetrical loss function
numerical calculations
Opis:: A complete algorithm is presented for the sharpening of imprecise information, based on the methodology of kernel estimators and the Bayes decision rule, including conditioning factors. The use of the Bayes rule with a nonsymmetrical loss function enables the inclusion of different results of an under- and overestimation of a sharp value (real number), as well as minimizing potential losses. A conditional approach allows to obtain a more precise result thanks to using information entered as the assumed (e.g. current) values of conditioning factors of continuous and/or binary types. The nonparametric methodology of statistical kernel estimators freed the investigated procedure from arbitrary assumptions concerning the forms of distributions characterizing both imprecise information and conditioning random variables. The concept presented here is universal and can be applied in a wide range of tasks in contemporary engineering, economics, and medicine.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2005, 15, 3; 393-404
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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