• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
KCDC, Accessed: Oct. 15, 2019. [Online]. Available: http://www.cdc.go.kr/npt/Google Search
2 
C. de Almeida Marques-Toledo, C. M. Degener, L. Vinhal, G. Coelho, W. Meira, C. T. Codeço, M. M. Teixeira, Jul. 2017, Dengue prediction by the web: Tweets are a useful tool for estimating and forecasting Dengue at country and city level, PLoS Neglected Tropical Diseases, Vol. 11, No. 7, pp. e0005729DOI
3 
I. S. O. Hayate, S. Wakamiya, E. Aramaki, 2016, Forecasting word model: Twitter-based influenza surveillance and prediction, in COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 76-86Google Search
4 
H. Achrekar, A. Gandhe, R. Lazarus, S.-H. Yu, B. Liu, 2011, Predicting flu trends using twitter data, in 2011 IEEE Conference on Computer Communications Workshops, pp. 702-707DOI
5 
S. Volkova, E. Ayton, K. Porterfield, C. D. Corley, Dec. 2017, Forecasting influenza-like illness dynamics for military populations using neural networks and social media, PloS one, Vol. 12, No. 12, pp. e0188941DOI
6 
A. Culotta, 2010, Towards detecting influenza epidemics by analyzing Twitter messages, in the First Workshop on Social Media Analytics, pp. 115-122DOI
7 
A. Wilder-Smith, E. Cohn, D. C. Lloyd, Y. Tozan, J. S. Brownstein, May. 2016, Internet-based media coverage on dengue in Sri Lanka between 2007 and 2015, Global Health Action, Vol. 9, No. 1, pp. 31620DOI
8 
J. Kim, I. Ahn, May. 2019, Weekly ILI patient ratio change prediction using news articles with support vector machine, BMC Bioinformatics, Vol. 20, No. 1, pp. 259DOI
9 
R. Chunara, J. R. Andrews, J. S. Brownstein, Jan. 2012, Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak, The American Journal of Tropical Medicine and Hygiene, Vol. 86, No. 1, pp. 39-45DOI
10 
J. Benesty, J. Chen, Y. Huang, I. Cohen, 2009, Pearson correlation coefficient, Noise Reduction in Speech Processing, Springer, pp. 1-4DOI
11 
T. Chai, R. R. Draxler, Feb 2014, Root mean square error (RMSE) or mean absolute error (MAE)?, Geoscientific Model Development Discussions, Vol. 7, pp. 1525-1534DOI
12 
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, J. Dean, 2013, Distributed representations of words and phrases and their compositionality, Advances in neural information processing systems, pp. 3111-3119Google Search
13 
E. L. Park, S. Cho, 2014, KoNLPy: Korean natural language processing in Python, the 26th Annual Conference on Human & Cognitive Language Technology, Vol. 6Google Search
14 
D. C. Montgomery, E. A. Peck, G. G. Vining, 2012, Introduction to linear regression analysis, John Wiley & Sons, Vol. 821Google Search
15 
R. Pascanu, C. Gulcehre, K. Cho, Y. Bengio, 2013, How to construct deep recurrent neural networks, arXiv preprint arXiv:1312.6026Google Search
16 
F. A. Gers, J. Schmidhuber, F. Cummins, 1999, Learning to forget: Continual prediction with LSTM, in Proc. of 9th International Conference on Artificial Neural NetworksDOI