과제정보
This work was supported by Gyeongnam SW Convergence Cluster 2.0 under the contract.
참고문헌
- A. Doni, C. Murthy and M. Z. Kurian, "Survey on multi sensor based air and water quality monitoring using IoT," Journal of Scientific Research in Science (JSRS), vol. 17, no. 2, pp. 147-153, 2018.
- M. Ahmed, M. O. Rahaman, M. Rahman, and M. A. Kashem, "Analyzing the Quality of Water and Predicting the Suitability for Fish Farming based on IoT in the Context of Bangladesh," in Proceeding of International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka: Bangladesh, Dec. 2019.
- Recurrent Neural Network Tutorial Part1-Introduction to RNNs [Internet]. Available: https://m.blog.naver.com/PostView.naver?isHttpsRedirect=true&blogId=rkdwnsdud555&logNo=221222845536.
- S. I. Ranapurwala, J. E. Cavanaugh, T. Young, H. Wu, C. Peek-Asa, and M. R. Ramirez, "Public health application of predictive modeling: an example from farm vehicle crashes," Journal of Injury Epidemiology (Part of Springer Nature), vol. 6, no. 1, pp. 1-11, Jun. 2019.
- A. Tamang and S. Shukla, "Water Demand Prediction Using Support Vector Machine Regression," in Proceeding of International Conference on Data Science and Communication (IconDSC), India : Bangalore, pp. 1-5, 2019.
- J. Zhang, Z. Zhang, Y. Weng, S. Gosling, H. Yang, C. Yang, W. Le, and Q. Ma, "Using Recurrent Neural Network for Intelligent Prediction of Water Level in Reservoir," in Proceeding IEEE 44th Annual Computer, Software, and Applications Conference (COMPSAC), Spain : Madrid, pp. 1125-1126, 2020.
- R. Rijayanti, A. Kadam, A. B. Wahyutama, B. Lee, and M. Hwang, "Design of the Environmental Data Monitoring and Prediction System for the Fish Farms," in Proceeding of KIICE Spring Conference, Korea : Yeosu City, pp. 178-180, 2021.
- S.A. Ludwig, "Comparison of Time Series Approaches applied to Greenhouse Gas Analysis: ANFIS, RNN, and LSTM," in Proceeding of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), USA: New Orleans, pp. 1-6, 2019.