Journal of Big Data Analytics in Transportation [electronic resource] /
Journal of Big Data Analytics in Transportation [electronic resource] /
edited by Satish V Ukkusuri, Leclercq Ludovic, Anuj Sharma.
- online resource.
Big Data Analytics in Transportation publishes high-quality original research and reviews in a wide range of topics where data driven methods and AI play a central role in transportation. The goal of the journal is to showcase the latest methodological advances and applications of big data methods in transportation and appropriate implications for policy making. The journal is also interested in the significant impact that these fields are beginning to have on other scientific disciplines as well as many aspects of society and industry. There are countless opportunities where big data intelligence can augment other methods in transportation systems planning, operations, freight, safety analysis, transit, safe and sustainable cities and emergency management. There are many emerging questions of relevance on ethical, social and privacy, that are also relevant in this domain. The focus is primarily on analytical data driven methods, high quality application based studies will also be considered. BDAT provides a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with original research articles, review papers and commentary articles.
2523-3564 = J. Big Data Anal. Transp.
42421 local
Transportation engineering.
Traffic engineering.
Computational intelligence.
Data mining.
Transportation Technology and Traffic Engineering.
Computational Intelligence.
Data Mining and Knowledge Discovery.
Big Data Analytics in Transportation publishes high-quality original research and reviews in a wide range of topics where data driven methods and AI play a central role in transportation. The goal of the journal is to showcase the latest methodological advances and applications of big data methods in transportation and appropriate implications for policy making. The journal is also interested in the significant impact that these fields are beginning to have on other scientific disciplines as well as many aspects of society and industry. There are countless opportunities where big data intelligence can augment other methods in transportation systems planning, operations, freight, safety analysis, transit, safe and sustainable cities and emergency management. There are many emerging questions of relevance on ethical, social and privacy, that are also relevant in this domain. The focus is primarily on analytical data driven methods, high quality application based studies will also be considered. BDAT provides a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with original research articles, review papers and commentary articles.
2523-3564 = J. Big Data Anal. Transp.
42421 local
Transportation engineering.
Traffic engineering.
Computational intelligence.
Data mining.
Transportation Technology and Traffic Engineering.
Computational Intelligence.
Data Mining and Knowledge Discovery.