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Wyszukujesz frazę "access prediction" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Predicting access to materialized methods by means of hidden Markov model
Autorzy:
Masewicz, M.
Andrzejewski, W.
Wrembel, W.
Królikowski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/970822.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
method materialization
hierarchical materialization
access prediction
hidden Markov model
Opis:
Method materialization is a promising data access optimization technique for multiple applications, including, in particular object programming languages with persistence, object databases, distributed computing systems, object-relational data warehouses, multimedia data warehouses, and spatial data warehouses. A drawback of this technique is that the value of a materialized method becomes invalid when an object used for computing the value of the method is updated. As a consequence, a materialized value of the method has to be recomputed. The materialized value can be recomputed either immediately after updating the object or just before calling the method. The moment the method is recomputed bears a strong impact on the overall system performance. In this paper we propose a technique of predicting access to materialized methods and objects, for the purpose of selecting the most appropriate recomputation technique. The prediction technique is based on the Hidden Markov Model (HMM). The prediction technique was implemented and evaluated experimentally. Its performance characteristics were compared to: immediate recomputation, deferred recomputation, random recomputation, and to our previous prediction technique, called a PMAP.
Źródło:
Control and Cybernetics; 2009, 38, 1; 127-152
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dredging Volumes Prediction for the Access Channel of Santos Port Considering Different Design Depths
Autorzy:
Pion, L.M.
Bernardino, J.C.M
Powiązania:
https://bibliotekanauki.pl/articles/116091.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Port of Santos
dredging
water level
dredging volumes prediction
Chart Datum (CD)
water level modeling
access channel
prediction method
Opis:
Santos is the most important Brazilian port, handling about 114 million of tons in 2016. In 2010, there was a great capital dredging in order to deepen the Access Channel to 15m deep (Chart Datum - CD). This depth was not achieved, due to inefficiency on dredging procedures. As deepening and maintaining design depths are indispensable, this study presents an analysis of sediment deposition in Santos Port Access Channel and an annual dredging volumes prediction, considering current bathymetric survey and design depths of 15, 16 and 17 m (CD).A numerical hydrodynamic and morphological model was developed for the interest area, by using Delft3D®, calibrated with waves, currents and water level data measured within Santos Port adjacen-cies. Sediment transport model was calibrated with suspended sediment data and historic series of dredged volumes from Santos Port Access Channel. Two different scenarios were simulated for each design depth, according to the regional environmental characteristics. For current bathymetric scenario, the model estimates that it would be necessary to dredge an annual average of about 4,325,000 m³ from Santos Port access chan-nel to maintain current depth condition. Regarding design depths of 15, 16, 17 meters, it would be an in-crease of 15%, 55%, and 80%.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2018, 12, 3; 505-514
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Yield prediction for winter wheat in Eastern Poland [Grabow] using the access-II model
Autorzy:
Henric, J.F.
Legros, J.P.
Slawinski, C.
Walczak, R.T.
Powiązania:
https://bibliotekanauki.pl/articles/25677.pdf
Data publikacji:
1996
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
root length
biomass calculation
Polska
Grabow
modelling
winter wheat
soil evaporation
ACCESS-II model
leaf growth
yield prediction
wheat
plant transpiration
stress
water content
Źródło:
International Agrophysics; 1996, 10, 3
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of models to study traffic accidents on the final sections of access roads to the cities: a case study of three major Iranian cities
Autorzy:
Fallah Tafti, Mehdi
Roshani, Reza
Powiązania:
https://bibliotekanauki.pl/articles/1955155.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
traffic accidents
city access roads
entrance roads
traffic safety
accident prediction model
neural networks
wypadki drogowe
drogi dojazdowe do miasta
drogi wjazdowe
bezpieczeństwo na drodze
modele przewidywania wypadków
sieci neuronowe
Opis:
The final sections of main access roads to the cities require especial attention as the frequency of accidents in these road sections are considerably higher than other parts of interurban roads. These road sections operate as an interface between the rural roads and urban streets. The previous researches available on this subject are limited and they have also mainly focused on a narrow range of factors contributing to the accidents in these areas. The main contribution of this research is to consider a relatively comprehensive range of potential factors , and to examine their impacts through the development and comparison of both conventional probabilistic models and Artificial Neural Network (ANN) models. For this purpose, information related to the main access roads of three major Iranian cities were collected. This information consisted of accident frequency data together with the field observations of traffic characteristics, roadway conditions and roadside features of these roads. Various ANN and probabilistic models were developed. The frequency of accidents, i.e. fatal, injured, or damaged accidents, was considered as the output of the developed models. The results indicated that a hybrid of ANN models, each comprised of 10 input variables representing traffic, roadway and roadside conditions, outperformed several probabilistic models, i.e. Poisson, Negative binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial models, also developed under similar conditions in this study. Moreover, effective roadway width, roadway lighting condition, the standard deviation of vehicles speed, percentage of drivers violating the speed limit, average annual daily traffic, percentage of heavy goods vehicles, the density of roadside commercial and industrial land uses, the density of median U-turns, the density of local access roads, and the effective width of the left-side shoulder were identified as the most effective factors contributing to the accidents in these areas. The developed ANN model can be used as a tool to predict accident rates in these road sections, and to estimate a potential reduction in the accident rates, following any improvements in the major factors contributing to the traffic accidents in these areas.
Źródło:
Archives of Transport; 2021, 59, 3; 129-148
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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