Igor Kabashkin & Irina Yatskiv 
Reliability and Statistics in Transportation and Communication [PDF ebook] 
Selected Papers from the 20th International Conference on Reliability and Statistics in Transportation and Communication, RelStat2020, 14-17 October 2020, Riga, Latvia

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This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most noteworthy methods and results discussed at the International Conference on Reliability and Statistics in Transportation and Communication (Rel Stat), which took place remotely from Riga, Latvia, on October 14 – 17, 2020. It spans a broad spectrum of topics, from mathematical models and design methodologies, to software engineering, data security and financial issues, as well as practical problems in technical systems, such as transportation and telecommunications, and in engineering education. 

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Table des matières

Simulation Experiments on Markov-Modulated Linear Regression Model.- Development of a Technological Solution for Automated Reintroducing of Mixed Lot Goods in the Trading Process.- Using Machine Learning For Do S Attacks Diagnostics.- Systematic Literature Review of Question Answering Systems.- Spatiotemporal Forecasting of Urban Traffic Flow Volatility.- Fast Connected Components Object Segmentation on Fused Lidar and Stereo-Camera Point Clouds With Visual-Inertial-Gimbal for Mobile Applications Utilizing GPU Acceleration.- Neuroevolutionary Approach to Metamodel-based Optimization in Production and Logistics.- An Artificial Intelligence Based Sourcing Automation Concept for Smaller and Mid-Sized Enterprises in the Metal Industry.- Overview of Spatial Decision Support System and Multiple Criteria Analysis in District Heating Network Maintenance.- Value Creation in Air Transportation: Beyond Price, Quality and Speed.

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Langue Anglais ● Format PDF ● Pages 879 ● ISBN 9783030684761 ● Taille du fichier 106.7 MB ● Éditeur Igor Kabashkin & Irina Yatskiv ● Maison d’édition Springer International Publishing ● Lieu Cham ● Pays CH ● Publié 2021 ● Téléchargeable 24 mois ● Devise EUR ● ID 7751225 ● Protection contre la copie DRM sociale

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