참고문헌
- M. S. Seo, "The Impact of Particulate Matter on Economic Activity," The Korean Women Economists Association, vol. 12, no. 1, pp. 75-100, Jun. 2015.
- A. Valavanidis, K. Fiotakis, and T. Vlachogianni, "Airborne Particulate Matter and Human Health: Toxicological Assessment and Importance of Size and Composition of Particles for Oxidative Damage and Carcinogenic Mechanisms," Journal of Environmental Science and Health, Part C, vol. 26, no. 4, pp. 339-362, Nov. 2008. https://doi.org/10.1080/10590500802494538
- K. H. Kim, E. Kabir, and S. Kabir, "A Review on the Human Health Impact of Airborne Particulate Matter," Environment International, vol. 74, pp. 136-143, Jan. 2015. https://doi.org/10.1016/j.envint.2014.10.005
- World Health Organization(WHO), "Health effects of particulate matter. Policy implications for countries in eastern Europe, Caucasus and central Asia," Regional Office for Europe, 2013.
- Board of Adit and Inspection(BAI), "Weather Forecast and Earthquake Notification System Operation," International THE Board of Audit and Inspection of KOREA, 2017.
- J. W. Cha and J. Y. Kim, "Development of Data Mining Algorithm for Implementation of Fine Dust Numerical Prediction Model," Journal of the Korea Institute of Information and Communication Engineering, vol. 22, no. 4, pp. 595-601, Apr. 2018. https://doi.org/10.6109/JKIICE.2018.22.4.595
- A. Chaloulakou, G. Grivas, and N. Spyrellis, "Neural Network and Multiple Regression Models for PM10 Prediction in Athens: A Comparative Assessment," Journal of the Air & Waste Management Association, vol. 53, no. 10, pp. 1183-1190, Oct. 2003. https://doi.org/10.1080/10473289.2003.10466276
- K. W. Cho, Y. J. Jung, J. S. Lee, and C. H. Oh, "Separation Prediction Model by Concentration based on Deep Neural Network for Improving PM10 Forecast Accuracy," Journal of the Korea Institute of Information and Communication Engineering, vol. 24, no. 1, pp. 8-14, 2020. https://doi.org/10.6109/JKIICE.2020.24.1.8
- K. Kaya and S. G. Oguducu, "A Binary Classification Model for PM10 Levels," in 2018 3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo, pp. 361-366, 2018.
- J. M. Han, J. G. Kim, and K. H. Cho, "Verify a Causal Relationship between Fine Dust and Air Condition-Weather Data in Selected Area by Contamination Factors," The journal of Bigdata, vol. 2, no. 1, pp. 17-26, Feb. 2017. https://doi.org/10.36498/kbigdt.2017.2.2.17
- X. Zhao, R. Zhang, J. L. Wu, and P. C. Chang, "A Deep Recurrent Neural Network for Air Quality Classification," Journal of Information Hiding and Multimedia Signal Processing, vol. 9, no. 2, pp. 346-354, Mar. 2018.
- B. T. Ong, S. Komei, and Z. Koji, "Dynamic Pre-training of Deep Recurrent Neural Networks for Predicting Environmental Monitoring Data," in 2014 IEEE International Conference on Big Data (Big Data), Washington DC, pp. 760-765, 2014.
- X. Li, L. Peng, X. Yao, S. Cui, Y.Hu, C. You, and T. chi, "Long Short-term Memory Neural Network for Air Pollutant Concentration Predictions: Method Development and Evaluation," Environmental Pollution, vol. 231, no. 1, pp. 997-1004, Dec. 2017. https://doi.org/10.1016/j.envpol.2017.08.114
- S. H. Jeon and Y. S. Son, "Prediction of Fine Dust PM10 using a Deep Neural Network Model," The Korean journal of applied statistics, vol. 31, no. 2, pp. 265-285, Apr. 2018. https://doi.org/10.5351/KJAS.2018.31.2.265
- J. R. Quinlan, "Learning Efficient Classification Procedures and Their Application to Chess End Games," in Machine Learning, Berlin, Springer, pp. 463-482, 1983.
- P. H. Huynh, V. H. Nguyen, and T. N. Do, "Enhancing Gene Expression Classification of Support Vector Machines with Generative Adversarial Networks," Journal of information and communication convergence engineering, vol. 17, no. 1, pp. 14-20, Mar. 2019. https://doi.org/10.6109/jicce.2019.17.1.14