신경망을 이용한 컨테이너 물동량 예측에 관한 연구 |
박성영, 이철영 |
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A Study on the Forecasting of Container Volume using Neural Network |
Sung-Young Park, Chul-Young Lee |
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Abstract |
The forecast of a container traffic has been very important for port and development. Generally, Statistic methods, such as moving average method, exponential smoothing, and regression analysis have been much used for traffic forecasting. But, considering various factors related to the port affect the forecasting of container volume, neural network of parallel processing system can be effective to forecast container volume based on various factors. This study discusses the forecasting of container volume by using the neural network with back propagation learning algorithm. Affected factors are selected based on impact vector on neural network, and these selected factors are used to forecast container volume. The proposed the forecasting algorithm using neural network was compared to the statistic methods. |
Key Words:
neural network;volume forecast;learning rate;backpropagation algorithm |
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