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 "Pham, Nguyen Dang Khoa" wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-2 z 2
    Tytuł:
    Role of green logistics in the construction of sustainable supply chains
    Autorzy:
    Pham, Nguyen Dang Khoa
    Dinh, Gia Huy
    Pham, Hoang Thai
    Kozak, Janusz
    Nguyen, Hoang Phuong
    Powiązania:
    https://bibliotekanauki.pl/articles/34606725.pdf
    Data publikacji:
    2023
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    green logistics
    supply chain
    environmental pollution
    sustainable development
    Opis:
    The global supply chain has been growing strongly in recent years. This development brings many benefits to the economy, society, and human resources in each country but also causes a large number of concerns related to the environment since traditional logistics activities in the supply chain have been releasing a significant amount of emissions. For that reason, many solutions have been proposed to deal with these environmental pollution problems. Among these, three promising solutions are expected to completely solve environmental problems in every supply chain: (I) Application of blockchain in the supply chain, (II) Use of renewable energy and alternative fuels, and (III) Design of a closed supply chain. However, it seems to lack a comprehensive study of these solutions aiming to overcome the drawbacks of traditional logistics. Indeed, this work focuses on analyzing and evaluating the three above-mentioned solutions and the impacts of each solution on solving problems related to traditional logistics. More importantly, this work also identifies critical factors and challenges such as policies, laws, awareness, and risks that are found to be remarkable difficulties in the shifting progress of traditional logistics to green logistics. Finally, directions for developing and deploying green solutions to the logistics, supply chain, and shipping sectors toward decarbonization strategies and net-zero goals are discussed in detail.
    Źródło:
    Polish Maritime Research; 2023, 3; 191-211
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using Artificial Neural Networks for predicting ship fuel consumption
    Autorzy:
    Nguyen, Van Giao
    Sakthivel, Rajamohan
    Rudzik, Krzysztof
    Kozak, Janusz
    Sharma, Prabhakar
    Pham, Nguyen Dang Khoa
    Nguyen, Phuoc Quy Phong
    Nguyen, Xuan Phuong
    Powiązania:
    https://bibliotekanauki.pl/articles/32918813.pdf
    Data publikacji:
    2023
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    artificial neural network
    fuel management
    marine engine
    ship fuel consumption
    energy efficiencys
    Opis:
    In marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types of ships. Most traditional statistical methods do not consider these factors when predicting marine vessel fuel consumption. With technological development, different statistical models have been developed for estimating fuel consumption patterns based on ship data. Artificial Neural Networks (ANN) are some of the most effective artificial methods for modelling and validating marine vessel fuel consumption. The application of ANN in maritime transport improves the accuracy of the regression models developed for analysing interactive relationships between various factors. The present review sheds light on consolidating the works carried out in predicting ship fuel consumption using ANN, with an emphasis on topics such as ANN structure, application and prediction algorithms. Future research directions are also proposed and the present review can be a benchmark for mathematical modelling of ship fuel consumption using ANN.
    Źródło:
    Polish Maritime Research; 2023, 2; 39-60
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

      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