Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1\,Hz Operational Data, CCGS \textit{Sir Wilfrid Laurier}
Ship fuel consumption (SFC) prediction supports vessel operation optimisation, emissions estimation, and decision support systems (DSS) for sustainable maritime transportation. Numerous data-driven fuel models have been developed over the past two decades, but a critical and often overlooked limitation lies in their validation practices: most studies evaluate performance using random train--test splits, which, applied to high-frequency records, admit temporal leakage and yield optimistic results that do not reflect deployment conditions. This paper examines that gap using time-aware evaluation
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- FuzzySimilar title/name (fuzzy) · 66%DataTalksClub/machine-learning-zoomcamp →
“Fuzzy title match (0.78): “Time-Aware Validation of Machine Learning Fuel Consumption M” ≈ “DataTalksClub/machine-learning-zoomcamp””
- FuzzySimilar title/name (fuzzy) · 66%stefan-jansen/machine-learning-for-trading →
“Fuzzy title match (0.78): “Time-Aware Validation of Machine Learning Fuel Consumption M” ≈ “stefan-jansen/machine-learning-for-trading””
- FuzzySimilar title/name (fuzzy) · 59%rasbt/python-machine-learning-book →
“Fuzzy title match (0.73): “Time-Aware Validation of Machine Learning Fuel Consumption M” ≈ “rasbt/python-machine-learning-book””
- FuzzySimilar title/name (fuzzy) · 59%aymericdamien/TopDeepLearning →
“Fuzzy title match (0.73): “Time-Aware Validation of Machine Learning Fuel Consumption M” ≈ “aymericdamien/TopDeepLearning””
- FuzzySimilar title/name (fuzzy) · 59%EthicalML/awesome-production-machine-learning →
“Fuzzy title match (0.73): “Time-Aware Validation of Machine Learning Fuel Consumption M” ≈ “EthicalML/awesome-production-machine-learning””
- LinkedLinked via arxiv author · 85%Samarasimha Reddy Chittamuru →
“Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1\,Hz Operational Data, CCGS \textit{Si”
- LinkedLinked via arxiv author · 85%Ayhan Akinturk →
“Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1\,Hz Operational Data, CCGS \textit{Si”
- LinkedLinked via arxiv author · 85%Allison Kennedy →
“Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1\,Hz Operational Data, CCGS \textit{Si”