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Ran (Angel) Yan 鄢然
Ran (Angel) Yan 鄢然
在 ntu.edu.sg 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship
R Yan, S Wang, Y Du
Transportation Research Part E: Logistics and Transportation Review 138, 101930, 2020
1272020
Route and speed optimization for liner ships under emission control policies
L Zhen, Z Hu, R Yan, D Zhuge, S Wang
Transportation Research Part C: Emerging Technologies 110, 330-345, 2020
1202020
Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation
S Wang, R Yan, X Qu
Transportation Research Part B: Methodological 128, 129-157, 2019
1082019
Data analytics for fuel consumption management in maritime transportation: Status and perspectives
R Yan, S Wang, HN Psaraftis
Transportation Research Part E: Logistics and Transportation Review 155, 102489, 2021
982021
Emerging approaches applied to maritime transport research: Past and future
R Yan, S Wang, L Zhen, G Laporte
Communications in Transportation Research 1, 100011, 2021
932021
An artificial intelligence model considering data imbalance for ship selection in port state control based on detention probabilities
R Yan, S Wang, C Peng
Journal of Computational Science 48, 101257, 2021
712021
Operation management of green ports and shipping networks: overview and research opportunities
L Zhen, D Zhuge, L Murong, R Yan, S Wang
Frontiers of Engineering Management 6 (2), 152-162, 2019
642019
A semi-“smart predict then optimize”(semi-SPO) method for efficient ship inspection
R Yan, S Wang, K Fagerholt
Transportation Research Part B: Methodological 142, 100-125, 2020
632020
Shipping domain knowledge informed prediction and optimization in port state control
R Yan, S Wang, J Cao, D Sun
Transportation Research Part B: Methodological 149, 52-78, 2021
552021
Implications of the EU’s inclusion of maritime transport in the emissions trading system for shipping companies
S Wang, L Zhen, HN Psaraftis, R Yan
Engineering 7 (5), 554-557, 2021
542021
Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports-A framework and a case study
X Wang, Z Liu, R Yan, H Wang, M Zhang
Ocean & coastal management 230, 106377, 2022
462022
Integrating prediction with optimization: Models and applications in transportation management
R Yan, S Wang
Multimodal Transportation 1 (3), 100018, 2022
452022
A smart predict-then-optimize method for targeted and cost-effective maritime transportation
X Tian, R Yan, Y Liu, S Wang
Transportation Research Part B: Methodological 172, 32-52, 2023
422023
Ship selection in port state control: status and perspectives
R Yan, S Wang, C Peng
Maritime Policy & Management 49 (4), 600-615, 2022
402022
Ship inspection by port state control—review of current research
R Yan, S Wang
Smart transportation systems 2019, 233-241, 2019
402019
A data mining method to extract traffic network for maritime transport management
Z Liu, H Gao, M Zhang, R Yan, J Liu
Ocean & Coastal Management 239, 106622, 2023
352023
Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
Y Song, Y Wu, Y Guo, R Yan, PN Suganthan, Y Zhang, W Pedrycz, S Das, ...
Swarm and Evolutionary Computation 86, 101517, 2024
252024
“Predict, then optimize” with quantile regression: A global method from predictive to prescriptive analytics and applications to multimodal transportation
S Wang, R Yan
Multimodal transportation 1 (4), 2022
242022
A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics
S Wang, R Yan
Cleaner logistics and supply chain 4, 2022
242022
Is port state control influenced by the COVID-19? Evidence from inspection data
R Yan, H Mo, X Guo, Y Yang, S Wang
Transport Policy 123, 82-103, 2022
222022
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