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Real-Time Explainable Concept Drift Detection for Eco-Driving in Mining Trucks using KSWIN and Event-Triggered SHAP

Fuel consumption represents a significant operational cost in mining, where real-time eco-driving optimization is hindered by dynamic and non-stationary operating conditions. Variations in operator behavior and environmental factors often induce concept drift, which diminishes the reliability of st...

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Principais autores: Kusnawi, Mochamad Agung Wibowo, Ridwan Sanjaya
Format: Artigo
Sprog:Inglês
Udgivet: Asosiasi Doktor Sistem Informasi Indonesia 2026-04-01
Serier:Journal of Information Systems and Informatics
Fag:
Online Learning
Concept Drift
Explainable AI
Eco-Driving
Streaming Data
Heavy Equipment
Online adgang:https://journal-isi.org/index.php/isi/article/view/1551
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