Wyniki 1-4 spośród 4 dla zapytania: authorDesc:"Bartosz ŚWIDERSKI"

Epileptic seizure detection using single-class SVM

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The paper presents the application of single-class Support Vector Machine (SVM) for the detection of the epileptic seizure using the EEG waveform. On the basis of the registered EEG signals the diagnostic features are generated first. These features are applied as the input signals to the single-class SVM, serving as the classification tool. Single class SVM is learned using only the baseline se[...]

Trend elimination of time series of 24-hour load demand in the power system and its application in power forecasting

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The paper is concerned with the elimination of different trends existing in the time series representing the hourly power consumption in the power system of small size. Analysing the hourly need for the power in such system we can observe significant trends associated with the season of the year, type of the day, as well as the particular hour of the day. At prediction task the variability of the time series is of great importance. The lower is this variability the better is the accuracy of prediction. In the paper we will present the method of reducing this variability by removing such trends. The elimination of trends is performed in few phases. The first step is to determine the index corresponding to the regular jth day of the weak for j = 1, 2, …, 7 and also type of such day. After this first step of detrending of the time series we follow the second and third aiming at removing the trend corresponding to the particular hour h of the day (h=1, 2, …, 24) and then the seasonality trend, characterizing the succeeding day of the year (d=1, 2, …, 365). All detrending operations are done by using the appropriately defined indexes. After application of all these steps we get the final detrended time series corresponding to all days under consideration (d=1, 2, …, p). The detrended time series is of much lower variance than the original one. This means the significant simplification of the forecasting problem and increase of probability of achieving better accuracy of forecasting results. The experiments of prediction of such detrended time series for small power region of Łódz performed using two types of neural predictors (MLP and SVM) have proved the superiority of such approach. Streszczenie. Praca dotyczy usuwania różnego rodzaju trendów występujących w szeregu czasowym odpowiadającym obciążeniom godzinnym w systemie elektroenergetycznym. Zwykły szereg czasowy charakteryzujący pobór mocy, zwłaszcza w małym systemie el[...]

Assessment of financial condition of companies using neural networks

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The paper presents the new automatic method of assessment of the financial condition of companies using neural networks. The aim of this assessment is to determine the insolvency risk of company. This information is important for worldwide transactions at which the insurance institution must assess the level of insurance risk of the import-export transaction. On the basis of this assessment the insurer can determine the insolvency of each side of transaction and decide of the height of the insurance. The paper will present an automatic method of such assessment by applying neural networks as the classifiers. The important part of this task is the optimal selection of the diagnostic features, on the basis of which the neural network will undertake the final decision and final classification of the company to the proper group. This is done by the neural classifiers. Streszczenie. Praca poświęcona jest opracowaniu metody oceniającej w sposób automatyczny kondycję finansową firmy za pomocą sieci neuronowych. Szacowanie kondycji finansowej firm pozwala na określenie ryzyka niewypłacalności firmy (jedna ze stron transakcji) czy też na decyzje ubezpieczyciela transakcji, czy taka transakcja warta jest ubezpieczenia oraz na jaką kwotę (instytucja ubezpieczająca transakcje międzynarodowe import-eksport). Istotny zatem jest przydział ryzyka niewypłacalności firmy do jednej z kilku klas, określającej stopień aktualnej kondycji finansowej firmy. W pracy zaproponowano system komputerowy, w którym na podstawie wielu cech diagnostycznych (nie tylko finansowych) klasyfikator neuronowy ocenia automatycznie poziom ryzyka związany z klasą. (Szacowanie kondycji finansowej przedsiębiorstw przy pomocy sieci neuronowych) Keywords: financial condition assessment, insolvency risk, neural networks. Słowa kluczowe: szacowanie kondycji finansowej, ryzyko niewypłacalności, sieci neuronowe. Introduction The well-know problem in business world is how to avoid customers,[...]

Box-counting fractal dimension in application to recognition of hypertension through the retinal image analysis

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The paper presents the application of the box-counting dimension to the recognition of hypertension through the analysis of the image of the eye fundus. The box-counting dimension represents a single measure, often used to describe the structure of fractal-like images. We propose based on it fast method of classification of the retinal image in order to recognize the class of healthy, introductory step and advanced illness cases. The results of experiments performed on 125 cases confirm good performance of the proposed method. Streszczenie. Praca prezentuje zastosowanie wymiaru pudełkowego do rozpoznania zmian ciśnieniowych poprzez automatyczna analizę obrazu dna oka. Zaproponowana została metoda szybkiego rozpoznania stanu chorobowego rozróżniająca trzy klasy: zdrowi, początkowy stan choroby i stan zaawansowany. Przedstawione są rezultaty rozpoznania dotyczące 125 przypadków. (Zastosowanie wymiaru pudełkowego do rozpoznania zmian ciśnieniowych poprzez automatyczna analizę obrazu dna oka) Keywords: retinal image processing, box-counting fractal dimension, image segmentation and classification Słowa kluczowe: obraz dna oka, fraktale, wymiar pudełkowy, segmentacja i rozpoznawanie obrazu Introduction Examination of the eye fundus images plays an important role in diagnosis of arterial hypertension and diabetes. Several changes are observed when illness start or is in an advanced stage. The detailed description of the degree of development of the illness, uses five-point scale [1]. The association of this scale with the view of the fundus of the eye is presented in Fig 1. The succeeding images represent typical vessel structures of eye fundus at different stages of the development of the artery hypertension. a) b) c) d) e) Fig.1. The typical images of the eye fundus at different stages of the development of the illness. a) Healthy stage, b) Stage 1 (angiopathia hypertonica retinae) c) Stage 2 (angiosclerosis hypertonica retinae) d) [...]

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