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Proceedings of the 11th International Conference on Traffic and Transportation Studies: Volume II 2024 ed. [Kõva köide]

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  • Formaat: Hardback, 569 pages, kõrgus x laius: 235x155 mm, 169 Illustrations, color; 58 Illustrations, black and white; X, 569 p. 227 illus., 169 illus. in color., 1 Hardback
  • Sari: Lecture Notes in Civil Engineering 617
  • Ilmumisaeg: 14-Nov-2024
  • Kirjastus: Springer Nature
  • ISBN-10: 9819796393
  • ISBN-13: 9789819796397
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  • Kõva köide
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  • Formaat: Hardback, 569 pages, kõrgus x laius: 235x155 mm, 169 Illustrations, color; 58 Illustrations, black and white; X, 569 p. 227 illus., 169 illus. in color., 1 Hardback
  • Sari: Lecture Notes in Civil Engineering 617
  • Ilmumisaeg: 14-Nov-2024
  • Kirjastus: Springer Nature
  • ISBN-10: 9819796393
  • ISBN-13: 9789819796397
Teised raamatud teemal:

This book reflects the latest research trends, methods and experimental results in the field of traffic and transport, covering a wealth of state-of-the-art research theories and ideas. As a vital field of research, highly relevant to current developments in a number of technological areas, the topics covered include traffic data analysis, transport planning, multimodal and integrated transport, modelling and analysis of passenger behaviour, etc. The aim of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academics and industry professionals to present the most innovative research and development in the field of traffic and transportation. Engineers and researchers from academia, industry and government will also explore the solutions that combine ideas from different disciplines in the field. The volumes serve as an excellent reference for researchers and graduate students working in the field of traffic and transportation.

Research on Automatic Transportation Scheme of Metro Station Based on Passenger-Freight Cooperation Mode.- Passenger Flow Assignment Model for Multi-routing Operation of Urban Rail Transit Based on Regret Theory.- Low-carbon Multimodal Transport Path Optimization Based on Genetic Particle Swarm Algorithm.- Demand Forecasting of Cold Chain Logistics for Agricultural Products Based on Gray BP Neural Networks.