Time Series Analysis in the Prediction of Water Quality

DOI

10.2991/emim-17.2017.11How to use a DOI?

Keywords

Time series analysis; ARIMA model; Water quality prediction

Abstract

The time series analysis method and the actual situation of the real-time monitoring system of the coastal waters are used to select the real-time monitoring data of the dissolved oxygen (DO) in the water quality monitoring data from 24th to 28th March 2016 as a research sample, the ARIMA model was fitted in the Eviews. The model was used to predict the data on March 29th and 30th and compared with the actual measured data. The results show that the relative error between the predicted value and the real value is 4-12% and the average error is about 4.79%. It is proved that the time series analysis is good enough in the water quality prediction. By comparing the results of static prediction and dynamic prediction, it is discussed that the limitation and future research of time series analysis method in water quality prediction problem.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qi An
AU  - Min Zhao
PY  - 2017/04
DA  - 2017/04
TI  - Time Series Analysis in the Prediction of Water Quality
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 51
EP  - 54
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.11
DO  - 10.2991/emim-17.2017.11
ID  - An2017/04
ER  -