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LISS2019 : Proceedings of the 9th International Conference on Logistics, Informatics and Service Sciences / / edited by Juliang Zhang, Martin Dresner, Runtong Zhang, Guowei Hua, Xiaopu Shang



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Titolo: LISS2019 : Proceedings of the 9th International Conference on Logistics, Informatics and Service Sciences / / edited by Juliang Zhang, Martin Dresner, Runtong Zhang, Guowei Hua, Xiaopu Shang Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Edizione: 1st ed. 2020.
Descrizione fisica: 1 online resource (965 pages) : illustrations
Disciplina: 413.0285
Soggetto topico: Management
Big data
Big Data
Persona (resp. second.): ZhangJuliang
DresnerMartin
ZhangRuntong
HuaGuowei
ShangXiaopu
Nota di contenuto: The Risk Sharing of Inter-city Railway PPP Project in China -- The Integration Degree of Logistics Industry and Regional Agglomeration Industry -- Government’s Role Choice in Market Regulation from an Information-Disclosure Perspective -- A Data-driven Methodology for Operational Risk Analytics Using Bayesian Network -- Order Batching of Intelligent Warehouse Order Picking System Based on Logistics Robots -- Modeling and Analysis on the Capacity of Centralized Directional Multi-hop Ad Hoc Networks -- Adaptive Routing Based on Wireless Ad Hoc Networks -- Grid Path Planning for Mobile Robots with Improved Q-learning Algorithm -- Content-based Weibo User Interest Recognition -- Intellectual Structure Detection Using Heterogeneous Data Clustering Method -- Technical Efficiency Analysis of Bus Companies.
Sommario/riassunto: This book focuses on AI and data-driven technical and management innovations in logistics, informatics and services. The respective papers analyze in detail the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. The book gathers the outcomes of the “9th International Conference on Logistics, Informatics and Service Sciences,” which was held at the University of Maryland, USA.
Titolo autorizzato: LISS2019  Visualizza cluster
ISBN: 981-15-5682-2
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910412148303321
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