A Design and Implement of Efficient Agricultural Product Price Prediction Model |
Im, Jung-Ju
(Dept. of Applied Artificial Intelligence, Hanyang University)
Kim, Tae-Wan (Dept. of Applied Artificial Intelligence, Hanyang University) Lim, Ji-Seoup (Dept. of Applied Artificial Intelligence, Hanyang University) Kim, Jun-Ho (Dept. of Computer Science & Engineering, Inha Technical College) Yoo, Tae-Yong (Dept. of Computer Science & Engineering, Inha Technical College) Lee, Won Joo (Dept. of Computer Science & Engineering, Inha Technical College) |
1 | M. Fafchamps and B. Minten, "Impact of SMS-Based Agricultural Information on Indian Farmers," In the World Bank Economic Review, Vol. 26, Issue.3, pp. 383-414, Nov. 2012 https://doi.org/10.1093/wber/lhr056 DOI |
2 | https://biz.newdaily.co.kr/site/data/html/2021/09/05/2021090500031.html. |
3 | https://www.kaggle.com/competitions |
4 | http://www.index.go.kr/potal/main/EachDtlPageDetail.do?idx_cd=1628 |
5 | Sutskever, I., Vinyals, O., & Le, Q. V., "Sequence to Sequence Learning with Neural Networks," NIPS. Dec. 2014, https://arxiv.org/abs/1409.3215 |
6 | Dorogush, A.V., Gulin, A., Gusev, G., Kazeev, N., Ostroumova, L., & Vorobev, A., "Fighting biases with dynamic boosting," June 2017, https://arxiv.org/pdf/1706.09516v1.pdf |
7 | "XGBoost Parameters," https://xgboost.readthedocs.io/en/stable/parameter.html |
8 | Friedman, J. H. (2002). "Stochastic gradient boosting," Computational statistics & data analysis, Vol. 38, No. 4, pp. 367-378, Feb. 2002 https://doi.org/10.1016/S0167-9473(01)00065-2 DOI |
9 | "Topic 10. Gradient Boosting," Kaggle, last modified Jul 01, 2020, accessed Oct. 09, 2021, www.kaggle.com/kashnitsky/topic-10-gradient-boosting |
10 | Jae Byung Lee, "A Study on Recent Boosting Methods," Thesis, Konkuk University, 2020 |
11 | Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., & Liu, T., "LightGBM: A Highly Efficient Gradient Boosting Decision Tree," Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017) |
12 | "CatBoost Training Parameters," https://CatBoost.ai/en/docs/references/training-parameters/ |
13 | https://www.mafra.go.kr/mafra/1336/subview.do |
14 | Chen, T., & Guestrin, C., "XGBoost: A Scalable Tree Boosting System," Proceedings of the 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 2016, https://arxiv.org/abs/1603.02754 |
![]() |