Disclosed are a short-term traffic flow prediction method using deep learning and a device thereof. A short-term traffic flow prediction method using deep learning includes the steps of: (a) determining a network structure of a deep learning-based model; and (b) applying a data set to the deep learning-based model to learn to predict the movement time of each node, converting the data set into genes, applying a genetic algorithm to derive weights and thresholds, and then applying the weights and thresholds to the deep learning-based model and learning the same to output short-term traffic flow prediction results, wherein step (b) may be repeated until a target value is reached.

    딥러닝을 이용한 단기 교통 흐름 예측 방법 및 그 장치가 개시된다. 딥러닝을 이용한 단기 교통 흐름 예측 방법은, (a) 딥러닝 기반 모델의 네트워크 구조를 결정하는 단계; 및 (b) 데이터 셋을 상기 딥러닝 기반 모델에 적용하여 각 노드의 이동 시간을 예측하도록 학습하되, 상기 데이터 셋을 유전자로 변환한 후 유전자 알고리즘을 적용하여 가중치와 임계치를 도출한 후 상기 딥러닝 기반 모델에 적용하여 학습시켜 단기 교통 흐름 예측 결과를 출력하는 단계를 포함하되, 상기 (b) 단계는 목표값에 도달할때까지 반복수행될 수 있다.


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    Title :

    Short-term traffic flow prediction method and device using deep learning


    Additional title:

    딥러닝을 이용한 단기 교통 흐름 예측 방법 및 그 장치


    Contributors:

    Publication date :

    2023-05-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

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



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