| Title |
Artificial Neural Network-based Real Time Water Temperature Prediction in the Soyang River |
| Authors |
정갑주(Jeong, Karpjoo) ; 이종현(Lee, Jonghyun) ; 이근영(Lee, Keun Young) ; 김범철(Kim, Bomchul) |
| DOI |
https://doi.org/10.5370/KIEE.2016.65.12.2084 |
| Keywords |
Real time environmental prediction ; Water temperature ; Artificial neural networks ; Cyberinfrastructure |
| Abstract |
It is crucial to predict water temperature for aquatic ecosystem studies and management. In this paper, we first address challenging issues in predicting water temperature in a real time manner and propose a distributed computing model to address such issues. Then, we present an Artificial Neural Network (ANN)-based water temperature prediction model developed for the Soyang River and a cyberinfrastructure system called WT-Agabus to run such prediction models in an automated and real time manner. The ANN model is designed to use only weather forecast data (air temperature and rainfall) that can be obtained by invoking the weather forecasting system at Korea Meteorological Administration (KMA) and therefore can facilitate the automated and real time water temperature prediction. This paper also demonstrates how easily and efficiently the real time prediction can be implemented with the WT-Agabus prototype system. |