The present invention includes: a linearization module which receives and linearizes first information which is information on a travel cost per transportation means from a traffic DB, a polynomial logic module which extracts second information which is probability density of a share rate according for each transportation means by receiving the first information which is linearized, and a deep learning module which processes the first information and the second information based on supervised learning. Accordingly, the present invention can improve the accuracy of a transportation means share rate calculation.

    본 발명은 교통 DB로부터 교통 수단별 통행비용에 대한 정보인 제 1 정보를 수신하여 선형화하는 선형화모듈, 상기 선형화된 제 1 정보를 수신하여 교통수단별 분담률의 확률밀도인 제 2 정보를 추출하는 다항로짓모듈, 상기 제 1 정보 및 제 2 정보를 지도 학습(Supervised Learning) 에 기반하여 처리하는 딥러닝모듈을 포함한다.


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    Title :

    APPARATUS AND METHOD FOR TRAVEL MODE CHOICE PREDICTION


    Additional title:

    교통수단분담 예측 장치, 방법 및 교통수단분담 예측을 위한 프로그램을 저장하는 저장매체


    Contributors:
    YI HONG SUK (author) / JUNG HEE JIN (author)

    Publication date :

    2017-05-31


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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