Research highlights ► In the field of transportation, data analysis is probably the most important and widely used research tool available. ► Differences and similarities between two ‘schools of thought’ – Statistics and Computational Intelligence – are revealed and discussed. ► Relevant literature in transportation research is reviewed and critically analyzed. ► A set of insights for selecting the appropriate approach for transportation applications is provided.

    Abstract In the field of transportation, data analysis is probably the most important and widely used research tool available. In the data analysis universe, there are two ‘schools of thought’; the first uses statistics as the tool of choice, while the second – one of the many methods from – Computational Intelligence. Although the goal of both approaches is the same, the two have kept each other at arm’s length. Researchers frequently fail to communicate and even understand each other’s work. In this paper, we discuss differences and similarities between these two approaches, we review relevant literature and attempt to provide a set of insights for selecting the appropriate approach.


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    Title :

    Statistical methods versus neural networks in transportation research: Differences, similarities and some insights


    Contributors:


    Publication date :

    2010-10-25


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English