20200728_Water Quality Prediction Method Based on LSTM Neural Network

 

1. Title, Journal and Authors

Title: Water Quality Prediction Method Based on LSTM Neural Network

Journal: 2017 IEEE

Authors: Yuanyuan Wang, Jian Zhou, Kejia Chen, Yunyun Wang, Linfeng Liu

*Jingsu High Technology Research Key Laboratory for Wireless Sensor Netoworks, College of Computer, Nanjing University of Posts and Telecommunications Nanjing

 

2. Summary

This paper mainly treats the LSTM model. LSTM mainly treats time-series data. Using DO and TP data in Taihu lake, the LSTM model is conducted and verified by adapting the parameters such as the number of hidden layers, epochs, and time step. In the result of comparing with BP NN and OS-ELM, LSTM shows the best performance in terms of R2 and RMSE.

 

 

5. Contact

Dae Seong Jeong / Integrated Ph.D. program

 

Environmental Systems Engineering Lab.

School of Earth Sciences and Environmental Engineering 

Gwangju Institute of Science and Technology

1 Oryong-dong Buk-gu Gwangju, 500-712, Korea

 

Phone : +82-10-2003-7860

E-mail : jeongds92@gist.ac.kr