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
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Asosiasi Doktor Sistem Informasi Indonesia 2026-04-01
סדרה:	Journal of Information Systems and Informatics
נושאים:	Online Learning Concept Drift Explainable AI Eco-Driving Streaming Data Heavy Equipment
גישה מקוונת:	https://journal-isi.org/index.php/isi/article/view/1551
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!