Wyniki wyszukiwania - BazTech

1

Two-dimensional modeling of car reliability during warranty period

Sliż Piotr, Wycinka Ewa, Jackowska Beata

Zeszyty Naukowe. Transport / Politechnika Śląska

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2023

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z. 121

223--239

EN

The paper focuses on presenting the concept of two-dimensional modeling of passenger car reliability during the warranty period. The main objective of this paper is to detect the regularity in the intensity of the number of first failure reports during the warranty period. The two-dimensional distribution of the time and mileage of failure-free exploitation is estimated. The period from the date of purchase to the first warranty repair is analysed. The concept presented incorporates the existing state of knowledge on two-dimensional warranties, expanding it through the use of a nonparametric approach and probability smoothing with the use of P-splines. The estimation involved censored data, i.e., data on vehicles that were not submitted for warranty repair within the warranty limits of time and mileage. The originality of this paper entails the combination of a nonparametric approach with probability smoothing. The statistical analyses presented in the paper were carried out on a population of 1005 vehicles of two car brands sold and serviced in 2011-2021 at the Authorized Service Station (Dealership). There were sales, repair, and warranty claim databases.

2

Bandwidth selection for kernel generalized regression neural networks in identification of hammerstein systems

Lv Jiaqing, Pawlak Mirosław

Journal of Artificial Intelligence and Soft Computing Research

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2021

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Vol. 11, No. 3

181--194

EN

This paper addresses the issue of data-driven smoothing parameter (bandwidth) selection in the context of nonparametric system identification of dynamic systems. In particular, we examine the identification problem of the block-oriented Hammerstein cascade system. A class of kernel-type Generalized Regression Neural Networks (GRNN) is employed as the identification algorithm. The statistical accuracy of the kernel GRNN estimate is critically influenced by the choice of the bandwidth. Given the need of data-driven bandwidth specification we propose several automatic selection methods that are compared by means of simulation studies. Our experiments reveal that the method referred to as the partitioned cross-validation algorithm can be recommended as the practical procedure for the bandwidth choice for the kernel GRNN estimate in terms of its statistical accuracy and implementation aspects.

3

A new approach to detection of changes in multidimensional patterns. Part 2

Gałkowski Tomasz, Krzyżak Adam, Patora-Wysocka Zofia, Filutowicz Zbigniew, Wang Lipo

Journal of Artificial Intelligence and Soft Computing Research

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2021

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Vol. 11, No. 3

217--227

EN

In the paper we develop an algorithm based on the Parzen kernel estimate for detection of sudden changes in 3-dimensional shapes which happen along the edge curves. Such problems commonly arise in various areas of computer vision, e.g., in edge detection, bioinformatics and processing of satellite imagery. In many engineering problems abrupt change detection may help in fault protection e.g. the jump detection in functions describing the static and dynamic properties of the objects in mechanical systems. We developed an algorithm for detecting abrupt changes which is nonparametric in nature and utilizes Parzen regression estimates of multivariate functions and their derivatives. In tests we apply this method, particularly but not exclusively, to the functions of two variables.

4

A new approach to detection of changes in multidimensional patterns

Gałkowski Tomasz, Krzyżak Adam, Filutowicz Zbigniew

Journal of Artificial Intelligence and Soft Computing Research

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2020

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Vol. 10, No. 2

125--136

EN

Nowadays, unprecedented amounts of heterogeneous data collections are stored, processed and transmitted via the Internet. In data analysis one of the most important problems is to verify whether data observed or/and collected in time are genuine and stationary, i.e. the information sources did not change their characteristics. There is a variety of data types: texts, images, audio or video files or streams, metadata descriptions, thereby ordinary numbers. All of them changes in many ways. If the change happens the next question is what is the essence of this change and when and where the change has occurred. The main focus of this paper is detection of change and classification of its type. Many algorithms have been proposed to detect abnormalities and deviations in the data. In this paper we propose a new approach for abrupt changes detection based on the Parzen kernel estimation of the partial derivatives of the multivariate regression functions in presence of probabilistic noise. The proposed change detection algorithm is applied to oneand two-dimensional patterns to detect the abrupt changes.

5

Nonparametric estimation of quantile versions of the Lorenz curve

Siedlaczek A. M.

Mathematica Applicanda

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2018

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Vol. 46, no. 1

149--157

EN

Estimators of quantile versions of the Lorenz curve are proposed. The pointwise consistency and asymptotic normality of the estimators is proved. The efficiency of the estimators is also studied in simulations.

PL

Zaproponowano nieparametryczne estymatory kwantylowych wersji krzywej Lorenza. Udowodniono punktową zgodność i asymptotyczną normalność zaproponowanych estymatorów. Porównano średnie scałkowane błędy kwadratowe wybranych nieparametrycznych estymatorów kwantylowych wersji krzywej Lorenza przy użyciu symulacji komputerowych.

6

Graphics processing units in acceleration of bandwidth selection for kernel density estimation

Andrzejewski W., Gramacki A., Gramacki J.

International Journal of Applied Mathematics and Computer Science

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2013

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Vol. 23, no. 4

869--885

EN

The Probability Density Function (PDF) is a key concept in statistics. Constructing the most adequate PDF from the observed data is still an important and interesting scientific problem, especially for large datasets. PDFs are often estimated using nonparametric data-driven methods. One of the most popular nonparametric method is the Kernel Density Estimator (KDE). However, a very serious drawback of using KDEs is the large number of calculations required to compute them, especially to find the optimal bandwidth parameter. In this paper we investigate the possibility of utilizing Graphics Processing Units (GPUs) to accelerate the finding of the bandwidth. The contribution of this paper is threefold: (a) we propose algorithmic optimization to one of bandwidth finding algorithms, (b) we propose efficient GPU versions of three bandwidth finding algorithms and (c) we experimentally compare three of our GPU implementations with the ones which utilize only CPUs. Our experiments show orders of magnitude improvements over CPU implementations of classical algorithms.

7

Nonparametric estimation for soil pore size distribution

Charytanowicz M.

Czasopismo Techniczne. Automatyka

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2013

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R. 110, z. 4-AC

17--27

EN

The study is concerned with the nonparametric kernel estimation to determine the soil porosity and pore size distribution. The kernel density estimation, the kernel estimation of cumulative distribution function, and the kernel estimator of quantile are considered. After a short description of the method, practical aspects and applications in agricultural science are presented. The nonparametric kernel estimation does not require a priori assumptions relating to the choice of the density function shape. Moreover, its natural interpretation together with its suitable properties makes them an adequate tool among others in estimation methods.

PL

Przedmiotem niniejszego artykułu jest zastosowanie nieparametrycznej estymacji jądrowej do scharakteryzowania rozkładu wielkości porów glebowych. W artykule przedstawiono jądrowy estymator gęstości i dystrybuanty oraz opisano algorytm wyznaczania jądrowego estymatora kwantyla, istotne ze względu na badanie porowatości agregatów glebowych. Zagadnienia te zostały zilustrowane przykładowymi zastosowaniami w naukach rolniczych. Nieparametryczna estymacja jądrowa nie wymaga a priori założeń dotyczących kształtu funkcji gęstości rozkładu prawdopodobieństwa i jest uzasadniona w sytuacji braku znajomości jej teoretycznego modelu. Ze względu na swobodę w doborze jądra oraz procedur wyznaczania parametrów estymatora możliwe jest dostosowanie jego własności do uwarunkowań konkretnego problemu.

8

Zastosowanie nieparametrycznych estymatorów jądrowych do analizy danych sondażowych

Gramacki A., Gramacki J.

Metody Informatyki Stosowanej

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2011

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nr 2

37-43

EN

The paper concerns nonparametric estimation of probability density functions (PDF). We demonstrate how one can use PDFs for easy and smart analysis of opinion polls data. Authors use PGSS dataset (Polish General Opinion Poll) made freely available in ADS [11] library. PGSS contains data collected during a large number of opinion polls carried out between 1992 and 2008. It contains answers for 1640 different questions asked to 16234 different citizens. From PGSS dataset we extracted data about Polish Presidential Elections held in 1990, 1995, 2000 and 2005. We analyze the support given to different candidates, as well as the fact of participation or not participation in the Elections as the function of citizens’ age. Based on PDF plots we try to describe political preferences of Poles.

9

Estymacja nieparametryczna wybranych parametrów bloku gazowo-parowego

Gramacki J., Gramacki A.

Pomiary Automatyka Kontrola

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2009

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R. 55, nr 7

454-456

PL

W pracy pokazano przykład użycia nieparametrycznej estymacji danych. Z pomocą tej techniki dokonano oszacowania emisji tlenków azotu (NOx) na podstawie danych eksploatacyjnych zbieranych podczas normalnej pracy Elektrociepłowni w Zielonej Górze. Na wstępnie dokonano krótkiego przeglądu najbardziej popularnych technik estymacji parametrycznej i porównano je z technikami nieparametrycznymi. Następnie na prostym przykładzie pokazano istotę działania estymacji nieparametrycznej. Pracę kończy rozdział, w którym krótko omówiono uzyskane wyniki symulacyjne.

EN

In the paper there are shown some practical examples of using nonparametric estimation. Using this technique there were estimated the nitrogen oxides (NOx) emissions based on the data taken from a real industry plant (gas and steam combined heat and power (CHP) plant in Zielona Góra, Poland). This work can be treated as a continuation of the paper [2]. In the first section there is given a short overview of estimation methods, including the linear and nonlinear regression, and comparison of them with nonparametric ones. In the second section there is briefly presented the nonparametric estimation technique and there is given a simple illustrative example. The third paragraph is dedicated to presenting the experimental results. Basing on the data from the CHP plant, the NOx emission was estimated and the satisfactory results (in comparison, for example, with the results obtained from the linear regression estimator) were obtained. All calculations were carried out using np package for R-project environment which implements a variety of nonparametric (and also semiparametric) kernel-based estimators.

10

Ocena rzeczywistej wydajności wybranych regresorów

Michalak M., Stąpor K.

Studia Informatica

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2008

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Vol. 29, nr 1

23-33

PL

Poniższa praca porusza temat nieparametrycznej estymacji funkcji regresji oraz jej efektywności czasowej. Autorzy porównują dokładność regresji, ale i czas potrzebny na wyznaczenie wartości dla obiektu testowego. Czas ten uwzględnia nie tylko samo wyznaczanie wartości, ale i etap tworzenia regresora. Eksperymenty zostały przeprowadzone na wielowymiarowych danych rzeczywistych.

EN

This paper raises a problem of nonparametric estimation of the regression function and its time efficiency. Authors compare the regression accuracy but considers also the time that is needed to evaluate the value for the test object. That time takes into consideration the evaluation time, but also the time of regressor creating. Experiments were conducted with the usage of multidimensional real data.

11

Applications of Kolmogorov Complexity and Universal Codes to Nonparametric Estimation of Characteristics of Time Series

Ryabko B.

Fundamenta Informaticae

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2008

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Vol. 83, nr 1-2

177-196

EN

We consider finite-alphabet and real-valued time series and the following four problems: i) estimation of the (limiting) probability P(x0 1/4xs) for every s and each sequence x0 1/4xs of letters from the process alphabet (or estimation of the density p(x0, 1/4, xs) for real-valued time series), ii) the so-called on-line prediction, where the conditional probability P(xt+1| x1x2 1/4xt) (or the conditional density p(xt+1| x1x2 1/4xt)) should be estimated, where x1x21/4xt are given, iii) regression and iv) classification (or so-called problems with side information). We show that Kolmogorov complexity (KC) and universal codes (or universal data compressors), whose codeword length can be considered as an estimation of KC, can be used as a basis for constructing asymptotically optimal methods for the above problems. (By definition, a universal code can "compress" any sequence generated by a stationary and ergodic source asymptotically to the Shannon entropy of the source.)

12

Identyfikacja rozkładu w systemach rzeczywistych za pomocą estymatorów jądrowych

Łukasik S.

Czasopismo Techniczne. Elektrotechnika

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2008

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R. 105, z. 1-E

3-13

PL

Metody nieparametryczne znajdują coraz szersze zastosowanie w zagadnieniach współczesnej analizy i eksploracji danych. W artykule przedstawiono najpopularniejsze narzędzie powyższych metod - estymatory jądrowe. Poza koncepcją tychże estymatorów zaprezentowano także praktyczne aspekty estymacji oraz przykłady jej zastosowań do wyznaczania rozkładów z dziedziny fizyki wysokich energii, wykrywania uszkodzeń silnika asynchronicznego oraz analizy danych socjologicznych.

EN

Nonparametric methods find increasing number of applications in the area of data analysis and data exploration. In this paper the most popular tool of those methods was presented - kernel estimators. Beside of kernel estimators' concept, practical estimation aspects and examples of applications in determining distributions from nuclear physics experiments, induction motors' damage detection and analysis of sociological data were shown as well.

13

Applicational possibilities of nonparametric estimation of distribution density for control engineering

Kulczycki P.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2008

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Vol. 56, nr 4

347-359

EN

Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density of a random variable distribution. Nonparametric methods allow here the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. Following an illustratory description of the fundamental procedures used to this end, results will be generalized and synthetically presented of research on the application of kernel estimators, dominant here, in problems of Bayes parameter estimation with asymmetrical polynomial loss function, as well as for fault detection in dynamical systems as objects of automatic control, in the scope of detection, diagnosis and prognosis of malfunctions. To this aim the basics of data analysis and exploration tasks – recognition of outliers, clustering and classification – solved using uniform mathematical apparatus based on the kernel estimators methodology were also investigated.

14

Metoda estymacji jądrowej w szacowaniu selektywności zapytań

Augustyn D.

Studia Informatica

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2002

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Vol. 23, nr 4

191-207

PL

W artykule dokonany został przegląd wybranych metod estymacji nieparametrycznej, wykorzystanych do szacowania współczynnika selektywności zapytań. Artykuł koncentruje się głównie na metodzie estymacji jądrowej, użytej do przybliżania nieznanej funkcji gęstości, opisującej rozkład wartości atrybutu tablicy bazy danych. Estymowana funkcja gęstości pozwala na oszacowanie selektywności zapytań wykorzystywanej przez optymalizator zapytań. Pokazana jest koncepcja wykorzystania metody estymacji jądrowej dla wyznaczania selektywności łącznie dla zbioru atrybutów, bez zakładania niezależności tychże, na podstawie wielowymiarowego estymatora jądrowego.

EN

The article presents a survey of methods of nonparametric estimation used' for estimation of query selectivity. The article mainly focuses on kernel estimation used for approximation of unknown density function of distribution of values from database table attribute. An approximation of density function lets calculate a query selectivity, used by database query optimizer. The paper presents multidimensional kernel estimator used for calculation of common query selectivity for set of attribute without the assumption of attributes independence.