Ranqi Ma
Dalian Maritime University
26 Papers
4 Citations
Ranqi Ma is an academic researcher from Dalian Maritime University. The author has contributed to research in topics: Computer science & Energy consumption. The author has an hindex of 3, co-authored 6 publications.
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Papers
A novel GA-LSTM-based prediction method of ship energy usage based on the characteristics analysis of operational data
Kai Wang,Yu Hua,Lian Zhong Huang,Xin Guo,Xingfu Liu,Zhongmin Ma,Ranqi Ma,Xiao Jiang +7 more
TL;DR: This study develops a GA-LSTM-based model for predicting ship energy usage, achieving 0.29% prediction error, outperforming existing BP, SVR, and ARIMA models, and enhancing ship energy efficiency optimization through accurate fuel usage forecasting.
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Joint energy consumption optimization method for wing-diesel engine-powered hybrid ships towards a more energy-efficient shipping
Kai Wang,Yunan Xue,Hao Xu,Lian Zhong Huang,Ranqi Ma,Peng Zhang,Xiao Jiang,Yupeng Yuan,Rudy R. Negenborn,Peiting Sun +9 more
TL;DR: In this paper , an energy consumption model is established based on the energy conversion analysis of the hybrid power system, and a joint optimization method of the wing attack angle and of the sailing speed for the hybrid ship is proposed by adopting a swarm intelligence optimization algorithm, in order to reduce energy consumption and CO2 emissions.
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A novel method for joint optimization of the sailing route and speed considering multiple environmental factors for more energy efficient shipping
Kai Wang,Kai Wang,Jiayuan Li,Lianzhong Huang,Ranqi Ma,Xiaoli Jiang,Yupeng Yuan,Ngome A. Mwero,Ngome A. Mwero,Rudy R. Negenborn,Peiting Sun,Xinping Yan +11 more
TL;DR: A novel joint optimization method of the sailing routes and speed, which considers the interaction between route and speed as well as multiple environmental factors, is proposed to fully exploit the energy efficiency's potential.
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An integrated collaborative decision-making method for optimizing energy consumption of sail-assisted ships towards low-carbon shipping
Kai Wang,Xin Guo,Junhao Zhao,Ranqi Ma,Lian Zhong Huang,Fengyu Tian,Siyi Dong,Peng Zhang,Chunlei Liu,Zhuang Wang +9 more
TL;DR: In this paper , a novel integrated collaborative decision-making method, considering the coupling influence of the sailing path, speed, wing-sail's angle of attack, and various environmental factors, is investigated to achieve energy conservation and emission reduction for sail-assisted ships.
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A novel dynamical collaborative optimization method of ship energy consumption based on a spatial and temporal distribution analysis of voyage data
Kai Wang,Hao Xu,Jiayuan Li,Lianzhong Huang,Ranqi Ma,Xiaoli Jiang,Yupeng Yuan,Ngome A. Mwero,Ngome A. Mwero,Peiting Sun,Rudy R. Negenborn,Xinping Yan +11 more
TL;DR: The results show that the newly developed dynamic collaborative optimization method, which fully considers the continuously time-varying characteristics of environmental and operational parameters, could effectively reduce the energy consumption in comparison to the original operational mode.
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