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Adaptive Sea Level Prediction Method Using Measured Data

관측치를 이용한 적응적 조위 예측 방법

  • 박상현 (순천대학교 멀티미디어공학과)
  • Received : 2017.08.08
  • Accepted : 2017.10.18
  • Published : 2017.10.31

Abstract

Climate changes consistently cause coastal accidents such as coastal flooding, so the studies on monitoring the marine environments are progressing to prevent and reduce the damage from coastal accidents. In this paper, we propose a new method to estimate the sea level which can be applied to the tidal sensors to monitor the variation of sea level. Existing sea level models are very complicated and need a lot of tidal data, so they are not proper for tidal sensors. On the other hand, the proposed algorithm is very simple but precise since we use the measured data from the sensor to estimate the sea level value in short period such as one or two hours. It is shown by experimental results that the proposed method is simple but predicts the sea level accurately.

기후변화 등으로 해안 침수 등의 피해가 증가하고 있으며, 이러한 피해를 줄이기 위해 해양을 지속적으로 모니터링하기 위한 연구들이 진행되고 있다. 본 논문에서는 해수면의 변화를 모니터링하기 위한 조위 센서에 적용할 수 있는 조위 예측 모델을 제안한다. 기존의 조위 예측 모델은 장기적인 예보를 위한 것으로 많은 데이터와 복잡한 알고리즘이 필요하다. 반면, 제안하는 알고리즘은 조위 센서에 탑재되어 동작할 수 있는 간단하지만 정확한 알고리즘으로, 센서에 의해 측정된 데이터를 기반으로 한 시간 또는 두 시간의 비교적 짧은 시간 후의 조위를 예측한다. 실험 결과는 제안하는 알고리즘이 간단하지만 정확하게 조위를 예측하는 것을 보여준다.

Keywords

References

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