Temat: Decision Supporting Algorithm - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: The Comparison of Safe Control Methods in Marine Navigation in Congested Waters
Autorzy:: Lisowski, J.
Powiązania:: https://bibliotekanauki.pl/articles/116043.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:: marine navigation
Congested Waters
Collision Situation
safe ship control
Decision Supporting Algorithm
Dynamic Programming Method
Linear Programming Method
Safe Own Ship's Trajectory
Opis:: The paper introduces comparison of five methods of safe ship control in collision situation: multi-stage positional non-cooperative and cooperative game, multi-step matrix game, dynamic and kinematics optimisation with neural constrains of state control process. The synthesis of computer navigator decision supporting algorithms with using dual linear programming and dynamic programming methods has been presented. The considerations have been illustrated an examples of a computer simulation the algorithms to determine the safe own ship's trajectory in situation of passing a many of the ships encountered at sea.
Źródło:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 2; 163-172
2083-6473
2083-6481
Pojawia się w:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: An Integrated Approach towards Building a Simulation Model Supporting the Management of the Passenger Transportation System. Part 2 – Case Study.
Autorzy:: Gąbka, Joanna
Susz, Sławomir
Rosienkiewicz, Maria
Powiązania:: https://bibliotekanauki.pl/articles/503826.pdf
Data publikacji:: 2016
Wydawca:: Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:: decision supporting tool
transportation system
algorithm verification
simulation model
Opis:: This article presents a simulation model designated as an advising and forecasting tool for designing, redesigning and managing ground-based transportation systems. It considers both public and private transport means. It enables visualisation of the results of changes in the transportation network such as a new transportation mode, schedule adjustment, technology improvements on shuttle speed and other modifications that can influence the effectiveness of the transportation network. The simulation tool enables predictions of future passenger flow size for different means of transport. The simulation tool was developed after thorough analysis of interdependencies between variables in the transportation network model built upon an econometric model, artificial neural network and mathematical model. The simulation model was tested on the real data and determined to be very effective, useful and flexible in use. Successive phases of the model development proved that development of a reliable advising and forecasting tool requires a combination of different methods.
Źródło:: Logistics and Transport; 2016, 32, 4; 51-64
1734-2015
Pojawia się w:: Logistics and Transport
Dostawca treści:: Biblioteka Nauki

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