Temat: PSO model - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Storage allocation in automated container terminals: the upper level
Autorzy:: Xia, M.
Zhao, N.
Mi, W.
Powiązania:: https://bibliotekanauki.pl/articles/258912.pdf
Data publikacji:: 2016
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:: storage allocation
automated container terminal
upper level model
PSO algorithm
Opis:: Nowadays automation is a trend of container terminals all over the world. Although not applied in current automated container terminals, storage allocation is indispensable in conventional container terminals, and promising for automated container terminals in future. This paper seeks into the storage allocation problem in automated container terminals and proposed a two level structure for the problem. A mixed integer programming model is built for the upper level, and a modified Particle Swarm Optimization (PSO) algorithm is applied to solve the model. The applicable conditions of the model is investigated by numerical experiments, so as the performance of the algorithm in different problem scales. It is left to future research the lower level of the problem and the potential benefit of storage allocation to automated container terminals.
Źródło:: Polish Maritime Research; 2016, S 1; 160-174
1233-2585
Pojawia się w:: Polish Maritime Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

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

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