Big Data Driven Smart Transportation: the Underlying Story of IoT Transformed Mobility

Big Data Driven Smart Transportation: the Underlying Story of IoT Transformed Mobility

Growing of smart IoT has generated many major impacts on transportation development, of which one underlying big story is the thriving of big data driven smart transportation nowadays. We are moving from IT to data technology (DT) time, and we are entering a “results driven” era in transportation. As the front and center of the smart IoT transformed mobility, transportation data sets grow rapidly while they are increasingly gathered from more con

Smart IoT in Transit Service: the Gateway to Improve Public Transportation

Smart IoT in Transit Service: the Gateway to Improve Public Transportation

Smart Internet of Things (IoT) in transit service has public transits connected to the networks accessible via internet. The networks connect to each other also the external environment to share data picked up by sensors on the transits themselves, offering many benefits to improve public transportation. Supported by the smart IoT connectivity integrated with Artificial Intelligence (AI), various on-board systems for transit vehicles have emerged

Work on leveraging optimization with mixed individual and social learning appears on Applied Soft Computing

Work on leveraging optimization with mixed individual and social learning appears on Applied Soft Computing

Our work on leveraging optimization with mixed individual and social learning in CGO appears on Applied Soft Computing. You can free access to the article through this link. X.-F. Xie, Z.-J. Wang. Cooperative group optimization with ants (CGO-AS): Leverage optimization with mixed individual and social learning. Applied Soft Computing, 2017, 50: 223-234. [DOI] We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Coopera

Presented our work on combinatorial optimization at International Joint Conference on Artificial Intelligence (IJCAI)

Presented our work on combinatorial optimization at International Joint Conference on Artificial Intelligence (IJCAI)

We presented our work on exploiting problem structure in combinatorial landscapes at the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York. X.-F. Xie, Z.-J. Wang. Exploiting problem structure in combinatorial landscapes: A case study on pure mathematics application. International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, USA, 2016: 2683-2689.   IJCAI is the premier conference bringing togeth