참고문헌
- Abhishek, K., M. P. Singh, S. Ghosh, and A. Anand, 2012: Weather forecasting model using artificial neural network. Procedia Technology 4, 311-318. https://doi.org/10.1016/j.protcy.2012.05.047
- Chen, J. L., H. B. Liu, W. Wu, and D. T. Xie, 2010: Estimation of monthly solar radiation from measured temperatures using support vector machines - A case study. Renewable Energy 36(2), 413-420.
- Han, J. H., J. J. Choi., U. Chung., K. S. Cho, and J. P. Chun, 2009: Frostfall forecasting in the Naju pear production area based on discriminant analysis of climatic data. Korean Journal of Agricultural and Forest Meteorology 11(4), 135-142. https://doi.org/10.5532/KJAFM.2009.11.4.135
- Chung, U., H. C. Seo, and J. I. Yun, 2004: Site- specific frost warning based on topoclimatic estimation of daily minimum temperature. Korean Journal of Agricultural and Forest Meteorology 6(3), 164-169.
- Kim, S. S., H. J. Kim, S. S. Chung, and Y. K. Lee, 2014; Multivariate Data Analysis with R. Korea National Open University Press, 191-210.
- Koo, J. Y., H. J. Park, D. W. Choi, and S. S. Kim, 2013: Data mining. Korea National Open University Press, 211-248 and 261-279.
- Kwon, Y. A., H. S. Lee., W. T. Kwon., and K. O. Boo, 2008: The weather characteristics of frost occurrence days for protecting crops against frost damage. Journal of the Korean Geographical Society 43(6), 824-842.
- Lee, J. G., 2016: R Program Recipes for Multi-Variate Analysis & Data Mining. Bullsbook, Seoul, 358pp.
- Naing, W. Y. N. and Z. Z. Htike, 2015: Forecasting of monthly temperature variations using random forests. ARPN journal of Engineering and Applied Sciences 10(21).
- Oh, I. S., 2013: Pattern Recognition, Kyobo Book Centre, Seoul, 95-132, and 137-170.
- Robinson, C. and N. Mort, 1996: A neural network solution to the problem of frost Prediction. UKACC International Conference on Control. Control '96, 136-139.
- Shank, D. B., G. Hoogenboom, and R. W. McClendon, 2008: Dewpoint Temperature Prediction Using Artificial Neural Networks. Journal of Applied Meteorology and Climatology 47(6), 1757-1769. https://doi.org/10.1175/2007JAMC1693.1
- Smith, B. A., R. W. McClendon, and G. Hoogenboom, 2007: Improving Air Temperature Prediction with Artificial Neural Networks. International Journal of Computational Intelligence 3, 180-186.
- Temeyer, B. R., W. A. Gallus Jr, K. A. Jungbluth, D. Burkheimer, and D. McCauley, 2003: Using an artificial neural network to predict parameters for frost deposition on Iowa bridgeways. Proceedings of the 2003 Mid-Continent Transportation Researchh Symposium, Iowa State University, Ames, IA, 2003.
- Yoo, J. E., 2015: Random forests, an alternative data mining technique to decision tree. Journal of Educational Evaluation 28(2), 427-448.
- Yong, H. S., Y. Nah, J. S. Park, H. W. Seung, M. Lee, S. Lee, and L. Choi, 2007: Data Mining, NFINITYBOOKS, 241-270 and 283-286.