Journal of Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회논문집)

Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회)
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The Prediction of Water Temperature at Saemangeum Lake by Neural Network

신경망모형을 이용한 새만금호 수온 예측

  • Oh, Nam Sun (Ocean.Plant Construction Engineering, Mokpo Maritime National University) ;
  • Jeong, Shin Taek (Department of Civil and Environmental Engineering, Wonkwang Univ.)
  • 오남선 (목포해양대학교 해양.플랜트건설공학과) ;
  • 정신택 (원광대학교 토목환경공학과, 원광대학교 부설 공업기술개발연구소)
  • Received : 2015.01.18
  • Accepted : 2015.02.25
  • Published : 2015.02.28
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Abstract

The potential impact of water temperature on sea level and air temperature rise in response to recent global warming has been noticed. To predict the effect of temperature change on river water quality and aquatic environment, it is necessary to understand and predict the change of water temperature. Air-water temperature relationship was analyzed using air temperature data at Buan and water temperature data of Shinsi, Garyeok, Mangyeong and Dongjin. Maximum and minimum water temperature was predicted by neural network and the results show a very high correlation between measured and predicted water temperature.

지구 온난화의 영향으로 해수면과 기온이 상승하고, 이의 직접적인 영향으로 수온이 증가하고 있다. 지구 온난화가 하천의 수질과 생태 환경에 미치는 영향을 추정하기 위해서는 수온에 대해 이해하고 수온의 변화를 예측할 필요가 있다. 이 연구에서는 수온의 변화를 예측하기 위하여 기온과 수온자료를 입력자료로 하여 수온의 예측을 실시하였다. 2012년에서 2014년까지 환경부의 수질환경관측소에서 관측한 새만금호내의 신시, 가력, 만경, 동진 4개 지점의 수온자료와 기상청에서 같은 기간에 관측한 부안의 자동관측 기온 자료를 활용하였다. 신경망이론을 이용하여 최고 및 최저 수온을 예측한 결과 4개 지점의 모든 결과에서 아주 높은 상관계수를 가지고 있다.

Keywords

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