Buch, Englisch, 349 Seiten, PB, Format (B × H): 170 mm x 240 mm
Reihe: Advances in information systems and management science
Guiding the Implementation of Machine Learning Algorithms
Buch, Englisch, 349 Seiten, PB, Format (B × H): 170 mm x 240 mm
Reihe: Advances in information systems and management science
ISBN: 978-3-8325-5630-3
Verlag: Logos
Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge.
In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms.
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Transport- und Verkehrswirtschaft
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Technische Wissenschaften Verkehrstechnik | Transportgewerbe Intelligente & automatisierte Transportsysteme
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Technische Wissenschaften Verkehrstechnik | Transportgewerbe Güterkraftverkehr, Spedition