참고문헌
- J. S. Park, K. R. Kang, S. Lee & S-R. Lee. (2013). Observation of the Sea Surface Skin Current Using a GPS-Drifter. Ocean and Polar Research, 35(4), 193-203. DOI : 10.4217/OPR.2013.35.3.193
- R. J. Little & D. B. Rubin. (2014). Statistical analysis with missing data. John Wiley & Sons. DOI : 10.1002/9781119013563
- J. W. Graham. (2009). Missing data analysis: Making it work in the real world. Annual review of psychology. Annual Review of Psychology, 60, 549-576. DOI : 10.1146/annurev.psych.58.110405.085530
- N. F. Schneidewind & H. M. Hoffmann, (1979). An experiment in software error data collection and analysis. IEEE Transactions on Software Engineering, 3, 276-286. DOI : 10.1109/tse.1979.234188
- J. H. Ha & Y. H. Kim, (2016). A Survey on Data Correction of Observation and Prediction Using Machine Learning: Preliminary Study for Optimizing Oil Spill Model. International Journal of Applied Engineering Research, 11(16), 8892-8895. DOI : 10.6088/ijaser.
- D. E. Rumelhart, G. E. Hinton & R. J. Williams. (1985). Learning Internal Representations by Error Propagation. DTIC Document, Tech. Rep. DOI : 10.21236/ada164453
- J. C. Platt. (1999). Fast Training of Support Vector Machines Using Sequential Minimal Optimization. Advances in Kernel Methods. 185-208.
- M. K. Lee, S. H. Moon, Y. H. Kim & B. R. Moon. (2014). Correcting Abnormalities in Meteorological Data by Machine Learning. In Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference, 888-893. DOI : 10.1109/smc.2014.6974024
- Y. H. Kim, J. H. Ha, Y. Yoon, N. Y. Kim, H. H. Im, S. Sim & R. K. Choi. (2016). Improved Correction of Atmospheric Pressure Data Obtained by Smartphones through Machine Learning. Computational intelligence and neuroscience, 2016(4). DOI : 10.1155/2016/9467878
- T. G. Barbounis, J. B. Theocharis, M. C. Alexiadis & P. S. Dokopoulos. (2006). Long-term wind speed and power forecasting using local recurrent neural network models. IEEE Transactions on Energy Conversion, 21(1), 273-284. DOI : 10.1109/tec.2005.847954
- T. Guo, Z. Xu, X. Yao, H. Chen, K. Aberer & K. Funaya. (2016). Robust Online Time Series Prediction with Recurrent Neural Networks. In Data Science and Advanced Analytics (DSAA), 2016 IEEE International Conference, 816-825. DOI : 10.1109/dsaa.2016.92
- G. D. Kim & Y. H. Kim, (2017). A Survey on Oil Spill and Weather Forecast Using Machine Learning Based on Neural Networks and Statistical Methods. Journal of the Korea Convergence Society, 8(10), 1-8. DOI : 10.15207/JKCS.2017.8.10.001
- Y. W. Nam & Y. H. Kim, (2018). Prediction of Drifter Trajectory Using Evolutionary Computation. Discrete Dynamics in Nature and Society 2018, 2018, In press.
- C. J. Lee, G. D. Kim & Y. H. Kim, (2017). Performance Comparison of Machine Learning Based on Neural Networks and Statistical Methods for Prediction of Drifter Movement. Journal of the Korea Convergence Society, 8(10), 45-52. DOI : 10.15207/JKCS.2017.8.10.045
- C. J. Lee & Y. H. Kim, (2017). Prediction of Drifter Trajectory Using an Ensemble Technique. Convergence Research Letter, 3(4), 671-674.