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Smart Fleet Management: Data-Driven Control of Rental Vehicles - Softcover

Kolesnykov, Vitalii

 
9786630015621: Smart Fleet Management: Data-Driven Control of Rental Vehicles

Inhaltsangabe

This monograph presents a comprehensive system for predictive maintenance scheduling in rental vehicle fleets, addressing the unique operational constraints of environments where the driver changes with every transaction. The work develops a multi-tier machine learning inference architecture combining per-vehicle variational autoencoder baselines for anomaly detection, an LSTM and gradient-boosted tree stacking ensemble for health index estimation with calibrated confidence intervals, and physics-informed regularization for rare failure modes. A composite maintenance scheduling priority score integrates mechanical urgency with rental-operational context, including reservation density, revenue tier, and fleet availability constraints, enabling autonomous orchestration of service events within compressed inter-rental maintenance windows. The monograph covers sensor modalities and data architectures, preprocessing and feature engineering pipelines, fleet-level demand forecasting, and data governance frameworks for connected fleet systems.

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Über die Autorin bzw. den Autor

Vitalii Kolesnykov - researcher and practitioner specializing in data-driven fleet management, predictive analytics, and intelligent transportation systems. His work focuses on the application of machine learning, sensor-based condition monitoring, and optimization methods to the operational challenges of commercial vehicle rental.

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