• Title/Summary/Keyword: Nodejs

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Design of Artificial Intelligence Water Level Prediction System for Prediction of River Flood (하천 범람 예측을 위한 인공지능 수위 예측 시스템 설계)

  • Park, Se-Hyun;Kim, Hyun-Jae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.2
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    • pp.198-203
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    • 2020
  • In this paper, we propose an artificial water level prediction system for small river flood prediction. River level prediction can be a measure to reduce flood damage. However, it is difficult to build a flood model in river because of the inherent nature of the river or rainfall that affects river flooding. In general, the downstream water level is affected by the water level at adjacent upstream. Therefore, in this study, we constructed an artificial intelligence model using Recurrent Neural Network(LSTM) that predicts the water level of downstream with the water level of two upstream points. The proposed artificial intelligence system designed a water level meter and built a server using Nodejs. The proposed neural network hardware system can predict the water level every 6 hours in the real river.