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Wyświetlanie 1-3 z 3
Tytuł:
Research on marine fhotovoltaic power forecasting based on Wavelet Transform and Echo State Network
Autorzy:
Du, X.
Wang, S.
Zhang, J.
Powiązania:
https://bibliotekanauki.pl/articles/260584.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
marine photovoltaic power system
power forecasting
Wavelet Transform
Echo State Network
Opis:
With the rapid development of photovoltaic power generation technology, photovoltaic power generation system has gradually become an important component of the integrated energy system of marine. High precision short-term photovoltaic power generation forecasting is becoming one of the key technologies in ship energy saving and ship energy efficiency improving. Aiming at the characteristics of marine photovoltaic power generation system, we designed a highprecision power forecasting model (WT+ESN) for marine photovoltaic power generation system with anti-marine environmental interference. In this model, the information mining of the photovoltaic system in marine environment is carried out based on wavelet theory, then the forecasting model basing on echo state network is construct ed. Lastly, three kinds of error metrics are compared with the three traditional models by Matlab, the result shows that the model has high forecasting accuracy and strong robustness to marine environmental factors, which is of great significance to save fuel for ships, improve the energy utilization rate and assist the power dispatching and fuel dispatching of the marine power generation system.
Źródło:
Polish Maritime Research; 2017, S 2; 53-59
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Deep Q-Learning Network for ship stowage planning problem
Autorzy:
Shen, Y.
Zhao, N.
Xia, M.
Du, X.
Powiązania:
https://bibliotekanauki.pl/articles/260614.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
Deep Q-Leaning Network (DQN)
container terminal
ship stowage plan
markov decision process
value function approximation
generalization
Opis:
Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem.
Źródło:
Polish Maritime Research; 2017, S 3; 102-109
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Study on optimization simulation of SCR denitration system for marine diesel engine
Autorzy:
Du, J.
Li, R. N.
Wu, X.
Zhang, Y.
Powiązania:
https://bibliotekanauki.pl/articles/259646.pdf
Data publikacji:
2018
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
marine diesel engine
SCR system
flue gas
flow deflector
Opis:
With the rapid development of shipbuilding industry exhaust world is also very harmful one kind of environmental issues, and the ship marine diesel engine exhaust gas is mainly produced, so in recent years it has developed a diesel engine SCR system. SCR system can control emissions of nitrogen oxides in the exhaust of vessel, furthermore air pollution can be reduced. The main goal of article was using fluent software to correct SCR system selection and flue gas flow under different size best deflector arrangement is simulated. Next goal is further optimize the structure of the SCR system.
Źródło:
Polish Maritime Research; 2018, S 3; 13-21
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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