Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "position prediction" wg kryterium: Wszystkie pola

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-6 z 6
    Tytuł:
    Error mitigation algorithm based on bidirectional fitting method for collision avoidance of Unmanned Surface Vehicle
    Autorzy:
    Song, L.
    Chen, Z.
    Mao, Y.
    Dong, Z.
    Xiang, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/260298.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    Unmanned Surface Vehicle
    position prediction
    error mitigation
    autoregressive model
    particle swarm optimization (PSO)
    Opis:
    Radars and sensors are essential devices for an Unmanned Surface Vehicle (USV) to detect obstacles. Their precision has improved significantly in recent years with relatively accurate capability to locate obstacles. However, small detection errors in the estimation and prediction of trajectories of obstacles may cause serious problems in accuracy, thereby damaging the judgment of USV and affecting the effectiveness of collision avoidance. In this study, the effect of radar errors on the prediction accuracy of obstacle position is studied on the basis of the autoregressive prediction model. The cause of radar error is also analyzed. Subsequently, a bidirectional adaptive filtering algorithm based on polynomial fitting and particle swarm optimization is proposed to eliminate the observed errors in vertical and abscissa coordinates. Then, simulations of obstacle tracking and prediction are carried out, and the results show the validity of the algorithm. Finally, the method is used to simulate the collision avoidance of USV, and the results show the validity and reliability of the algorithm.
    Źródło:
    Polish Maritime Research; 2018, 4; 13-20
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of crack depth and position in vibrating beams using artificial neural networks
    Autorzy:
    Bouboulas, Athanasios
    Nikolakopoulos, Pantelis
    Anifantis, Nikolaos
    Powiązania:
    https://bibliotekanauki.pl/articles/2146739.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    crack prediction
    contact conditions
    finite element method
    artificial neural networks
    pęknięcia
    warunki kontaktu
    metoda elementów skończonych
    sztuczne sieci neuronowe
    Opis:
    The aim of this paper is to develop a finite element procedure for crack prediction in vibrating beams. Based on this procedure, full frictional contact conditions are introduced between the crack surfaces in order to consider the breathing of crack. The region surrounding the crack is simulated by two-dimensional finite elements. An incremental-iterative procedure is employed to solve the nonlinear dynamic equations governing this problem. The obtained time response is processed with Fast Fourier Transform to extract its frequency components. The first three natural frequencies are input to a trained Artificial Neural Network for depth and position prediction of the crack. This study is validated for a dynamic loading cantilever beam. It is found that the proposed procedure is capable of predicting the crack depth and position with high accuracy.
    Źródło:
    Diagnostyka; 2022, 23, 3; art. no 2022307
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of deflection from flatness and a vertical position with the use of neural networks
    Predykcja odchyleń od płaskości i pozycji pionowej z zastosowaniem sieci neuronowych
    Autorzy:
    Mrówczyńska, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/396318.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    neural networks
    deflections from flatness
    prediction
    church of the Blest Virgin Mary in Toruń
    sieci neuronowe
    odchylenia od płaskości
    predykcja odchyleń
    kościół Najświętszej Maryi Panny w Toruniu
    Opis:
    The paper presents an attempt to apply unidirectional multilayer neural networks in the prediction of the deflections from flatness and from a vertical position of building walls, on an example of periodic measurements in the church of the Blessed Virgin Mary in Toruń. The applied methods of artificial intelligence in a form of sigmoid neural networks were taught with the use of the backpropagation method, which bases on the gradient methods described in optimization theories. The prognosis of the values of the deflections from flatness and from vertical position was carried out for a single measurement epoch on the basis of ten periodic measurements performed at several-year intervals.
    W artykule podjęto próbę wykorzystania sieci neuronowych jednokierunkowych wielowarstwowych do predykcji odchyleń od płaskości i pozycji pionowej ścian budynku, na przykładzie pomiarów okresowych kościoła Najświętszej Maryi Panny w Toruniu. Wykorzystane metody sztucznej inteligencji w postaci sieci neuronowych typu sigmoidalnego były uczone metodą propagacji wstecznej błędu, która bazuje na znanych z teorii optymalizacji metodach gradientowych. Prognoza wielkości wychyleń od pionu i płaskości została przeprowadzona dla jednej epoki pomiarowej na podstawie dziesięciu pomiarów okresowych wykonanych w kilkuletnich odstępach czasu.
    Źródło:
    Civil and Environmental Engineering Reports; 2012, 9; 73-81
    2080-5187
    2450-8594
    Pojawia się w:
    Civil and Environmental Engineering Reports
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Proposal of the prediction algorithm of the object’s position in restricted area
    Autorzy:
    Dramski, M.
    Mąka, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/393878.pdf
    Data publikacji:
    2015
    Wydawca:
    Polskie Stowarzyszenie Telematyki Transportu
    Tematy:
    prognoza
    obszar zastrzeżony
    nawigacja
    transport
    najkrótsza ścieżka
    prediction
    restricted area
    navigation
    shortest path
    Opis:
    In this paper an algorithm of finding the optimal path of an object in restricted area, focusing on the position prediction, is presented. Moving in the restricted area requires not only the knowledge of this area, but also the current and future position of other objects present in it. These informations let to minimalize the possible collision risk. It’s significant not only due to the safety, but also to the economic factors. This approach is the further development of the investigations in the area of finding the optimal path in restricted area, carried out at the Maritime University of Szczecin. The authors propose the algorithm for the use in the decision support systems in maritime navigation, but it could be also applied in the other areas of transport.
    Źródło:
    Archives of Transport System Telematics; 2015, 8, 2; 13-16
    1899-8208
    Pojawia się w:
    Archives of Transport System Telematics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Source Rock Prediction Value: world provinces during Late Jurassic–earliest Cretaceous times and position of West Carpathians in SRPV prediction
    Autorzy:
    Golonka, J.
    Krobicki, M.
    Waśkowska, A.
    Matyasik, I.
    Pauken, R.
    Bocharova, N. J.
    Edrich, M.
    Wildharber, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/191466.pdf
    Data publikacji:
    2009
    Wydawca:
    Polskie Towarzystwo Geologiczne
    Opis:
    Thirty-six Late Jurassic–Early Cretaceous regions were evaluated to obtain the Source Rocks Predic- tion Value (SRPV). We focused on three major processes, which control the organic richness in a specific paleogeographic, climatic and tectonic setting. These three processes are biologic productivity, background sedimentation rates with non-dilution of organic richness by clastic sedimentation, and preservation of organic matter. A high or increased level of primary biologic productivity supports an increased flux of organic carbon to the sediments of the sea floor. When sedimentation rate increases, especially of fine-grained sediment, the organic matter content of the sediment also increases. Preservation of organic matter depends on domination of anoxic conditions during periods of stagnation of Carpathian basins. The debate over which of the three primary pro- cesses is the most important control on the accumulation of organic-rich facies is inconclusive. We assume that the three processes are equally important, and that the balance between them has the overriding control. The amount and richness of organic matter buried in marine sediments then depends on the balance between production and destruction, where the latter includes consumption, decomposition, and dilution. The modeling of the Source Rocks Prediction Value has placed the marginal Tethyan Ocean (Carpathian basin) among the basins, which contain the richest Late Jurassic–Early Cretaceous source rocks in the world. Using the semi-quantitative Delphi method for 36 Late Jurassic regions, which represents a single tectono-depositional province in this time, we evaluated the assessment of SRPV for each of these. The south-Caspian and Central Asia basin was ranked eighth, while the Carpathian basin ninth. The paleogeographic and paleoclimatic settings are indicated as main factors in distribution by basins of known organic-rich rocks. The high organic productivity of the Carpathian basins was caused by upwelling, as well as restricted conditions in the narrow rift basins. The Upper Jurassic organic-rich Mikulov marls representing world-class source rocks (in the southeastern Czech Republic and north-eastern Austria) and Upper Jurassic–lowermost Cretaceous Vendryně Formation rocks were used as local example in analysis of oil source deposits within West Carpathian arc. The average measured Source Potential Index (SPI) for both investigated Upper Jurassic organic rich formations is around 10 and this value fits very well the SPI pre- dicted for Carpathian Upper Jurassic using Source Rocks Prediction Value method.
    Źródło:
    Annales Societatis Geologorum Poloniae; 2009, 79, No 2; 195-211
    0208-9068
    Pojawia się w:
    Annales Societatis Geologorum Poloniae
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The influence of application a simplified transformation model between reference frames ECEF and ECI onto prediction accuracy of position and velocity of GLONASS satellites
    Autorzy:
    Krzyżek, R.
    Skorupa, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/106729.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Warszawska. Wydział Geodezji i Kartografii
    Tematy:
    broadcast ephemeris
    transformation
    ECEF
    ECI
    GLONASS
    efemerydy
    transmisja
    transformacja
    Opis:
    In computational tasks of satellite geodesy there is a need for transformation of coordinates between reference frames ECEF – Earth Centered, Earth Fixed and ECI – Earth Centered, Inertial. Strict and simplified transformation models, which can be used in case of the position and velocity short-term predictions of GLONASS satellites, have been presented in this study. Comparison of the results of state vector components predictions of the GLONASS satellites, in dependence of the used transformation model, have also been presented. Accuracy of the prediction has been determined on the basis of the analyse of deviations of the predicted positions and velocities of GLONASS satellites from their values given in broadcast ephemeris.
    Źródło:
    Reports on Geodesy and Geoinformatics; 2015, 99; 19-27
    2391-8365
    2391-8152
    Pojawia się w:
    Reports on Geodesy and Geoinformatics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies