The Experts below are selected from a list of 48 Experts worldwide ranked by ideXlab platform
Wenyuan Wang - One of the best experts on this subject based on the ideXlab platform.
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Machine learning method for energy consumption prediction of ships in port considering green ports
Journal of Cleaner Production, 2020Co-Authors: Yun Peng, Huakun Liu, Jian Huang, Wenyuan WangAbstract:Abstract Two main contributions of this paper are 1) the energy consumption of ships (ECS) in port is predicted, 2) reduction strategies for energy consumption of ships in port are discussed by the proposed prediction models considering green port. Firstly, 15 characteristics which have impact on the energy consumption of ships are collected by Jingtang Port in China and analysis is conducted. Then, five machine learning models including Gradient Boosting Regression (GBR), Random Forest Regression (RF), BP Network (BP), Liner Regression (LR) and K-Nearest Neighbor Regression (KNN) are developed and 15 features consisting of inherent property of ship and external features of ports are set as inputs. After then, k-folds cross validation is adopted to verify the effectiveness of models. Finally, the feature importance is calculated and the most important features are selected. Besides, experiments are conducted to find the effect of changing several features on energy consumption of ships, and two consumption reduction strategies are discussed. The results show that Net Tonnage, deadweight Tonnage, actual weight and efficiency of facilities are the top 4 features for predicting the energy consumption of ships. In conclusion, when efficiency of facilities is doubled, the energy consumption of ships is reduced by 34.17% at berth and 8.41% in port. The finding of proposed methods and discussed strategies can give references to green port construction.
Alit Hindri Yani - One of the best experts on this subject based on the ideXlab platform.
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APPLICATION OF CALCULATION GROSS Tonnage (GT) AND Net Tonnage (NT) FISHING BOAT SYSTEM BASED ON WEB
2015Co-Authors: Patrialis Akbari, Ronald M Hutauruk, Alit Hindri YaniAbstract:AbstrackThis research was conducted month december 2014 - february 2015 in the laboratory of Fishing boat. The research purpose is to design an application that is easy to use in the calculation of Tonnage of fishing boat, namely gross Tonnage (GT) and Net Tonnage (NT). The method used is descriptive method. The results showed that with this application can determine the size of the Tonnage of the boat is gross Tonnage (GT) and Net Tonnage (NT) are approaching the actual size easily, quickly and clearly. After validating the data from department of fisheries and marine, obtained difference calculation accuracy by 5 %, so the application can be applied in the calculation Tonnage fishing boat. The application can be used for data collection boat owners and taxation. The application can be used by fishermen, government and student fisheries.Keywords : Application, Tonnage, Fishing boats
Jonny Zain - One of the best experts on this subject based on the ideXlab platform.
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Design of Purse Seiner in the Sibolga Arcipelago Fishing Port Province North Sumatera
2017Co-Authors: Renta Lina, Polaris Nasution, Jonny ZainAbstract:The Successfull of fishing catch effort very be effected by the fisheries resources available, fishing fleet and fishing gear used a accordance waters condition and species of fish in the waters. For optimally utilize the resources potential of the research needed determination carryng capacity, an adequate number and size of the fishing ship needed. Waters of the west Sumatera coast has potential of fishing is utilized along 23% of the available potential, which is dominated catches small pelagic. So, have needed this research to develop the purse seine fisheries business in particular. The method used in this research is a survey method of data collection and direct observation to the field, then the data is processed using regression analysis, comperative ship, designing ship with the NSP method. For the next 25 years, along with the effectiveness lifespan of the vessel, need an additional 21 purse seiner, 88 gross Tonnage, 52,117 Net Tonnage, 21 meters LPP, 6,924 meters breath, 2,18 meters high and 1,86 meters maximum draft.
Yun Peng - One of the best experts on this subject based on the ideXlab platform.
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Machine learning method for energy consumption prediction of ships in port considering green ports
Journal of Cleaner Production, 2020Co-Authors: Yun Peng, Huakun Liu, Jian Huang, Wenyuan WangAbstract:Abstract Two main contributions of this paper are 1) the energy consumption of ships (ECS) in port is predicted, 2) reduction strategies for energy consumption of ships in port are discussed by the proposed prediction models considering green port. Firstly, 15 characteristics which have impact on the energy consumption of ships are collected by Jingtang Port in China and analysis is conducted. Then, five machine learning models including Gradient Boosting Regression (GBR), Random Forest Regression (RF), BP Network (BP), Liner Regression (LR) and K-Nearest Neighbor Regression (KNN) are developed and 15 features consisting of inherent property of ship and external features of ports are set as inputs. After then, k-folds cross validation is adopted to verify the effectiveness of models. Finally, the feature importance is calculated and the most important features are selected. Besides, experiments are conducted to find the effect of changing several features on energy consumption of ships, and two consumption reduction strategies are discussed. The results show that Net Tonnage, deadweight Tonnage, actual weight and efficiency of facilities are the top 4 features for predicting the energy consumption of ships. In conclusion, when efficiency of facilities is doubled, the energy consumption of ships is reduced by 34.17% at berth and 8.41% in port. The finding of proposed methods and discussed strategies can give references to green port construction.
Patrialis Akbari - One of the best experts on this subject based on the ideXlab platform.
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APPLICATION OF CALCULATION GROSS Tonnage (GT) AND Net Tonnage (NT) FISHING BOAT SYSTEM BASED ON WEB
2015Co-Authors: Patrialis Akbari, Ronald M Hutauruk, Alit Hindri YaniAbstract:AbstrackThis research was conducted month december 2014 - february 2015 in the laboratory of Fishing boat. The research purpose is to design an application that is easy to use in the calculation of Tonnage of fishing boat, namely gross Tonnage (GT) and Net Tonnage (NT). The method used is descriptive method. The results showed that with this application can determine the size of the Tonnage of the boat is gross Tonnage (GT) and Net Tonnage (NT) are approaching the actual size easily, quickly and clearly. After validating the data from department of fisheries and marine, obtained difference calculation accuracy by 5 %, so the application can be applied in the calculation Tonnage fishing boat. The application can be used for data collection boat owners and taxation. The application can be used by fishermen, government and student fisheries.Keywords : Application, Tonnage, Fishing boats
