Working Paper Article Version 1 This version is not peer-reviewed

ARIMA-M: A New Model for Daily Water Consumption Prediction, Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction

Version 1 : Received: 9 January 2020 / Approved: 10 January 2020 / Online: 10 January 2020 (07:09:20 CET)

How to cite: Du, H.; Zhao, Z.; Xue, H. ARIMA-M: A New Model for Daily Water Consumption Prediction, Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction. Preprints 2020, 2020010095 Du, H.; Zhao, Z.; Xue, H. ARIMA-M: A New Model for Daily Water Consumption Prediction, Based on the Autoregressive Integrated Moving Average Model and the Markov Chain Error Correction. Preprints 2020, 2020010095

Abstract

Water resource is considered as a significant factor in development of regional environment and society. Water consumption prediction can provide important decision basis for the regional water supply scheduling optimisations. According to the periodicity and randomness nature of the daily water consumption data, a Markov modified autoregressive moving average (ARIMA) model is proposed in this study. The proposed model, combined with the Markov chain, can correct the prediction error, reduce the continuous superposition of prediction error, and improve the prediction accuracy of future daily water consumption data. The daily water consumption data of different monitoring points are used to verify the effectiveness of the model, and the future water consumption is predicted, in the study area. The results show that the proposed algorithm can effectively reduce the prediction error compared to the ARIMA.

Subject Areas

water resource management; water consumption prediction; Markov chain; autoregressive moving average model; error correction

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.