The prediction of water temperature is crucial for aquatic ecosystem studies and management. In this paper, we raise challenging issues in supporting real time water temperature prediction and present a system called WT-Agabus to address those issues. The WT-Agabus system is designed to be a cyberinfrastructure and to support various prediction models in a uniform way. In addition, we present a neural network-based water temperature prediction model to use only data available online from Korea Meteorological Administration (KMA). In this paper, we also show the current prototype implementation of the WT-Agabus system to support the prediction model
Cite
@article{arxiv.1509.07616,
title = {A Cyberinfrastructure-based Approach to Real Time Water Temperature Prediction},
author = {Jounghyun Lee and Keun Young Lee and Karpjoo Jeong and Meilan Jiang and Bomchul Kim and Suntae Hwang},
journal= {arXiv preprint arXiv:1509.07616},
year = {2015}
}