2017
DOI: 10.24850/j-tyca-2017-05-09
|View full text |Cite
|
Sign up to set email alerts
|

Arima as a forecasting tool for water quality time series measured with UV-Vis spectrometers in a constructed wetland

Abstract: Arima as a tool to predict water quality using time series recorded with UV-Vis spectrometers in a constructed wetland. Water Technology and Sciences (in Spanish), 8(5), 127-139.The prediction of water quality plays a crucial role in discussions about urban drainage systems, given that the integrated management of this resource is required in order to meet human needs. The present paper uses Arima (Autoregressive Integrated Moving Average) to predict influent and effluent water quality in a constructed wetland… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
4
2

Relationship

0
6

Authors

Journals

citations
Cited by 9 publications
(2 citation statements)
references
References 25 publications
0
1
0
Order By: Relevance
“…One of the most important and widely used time series models is the autoregressive integrated moving average (ARIMA) model Introduced by Box and Jenkins. ARIMA model is a traditional time series forecasting method and applied in various fields [35][36]. In an ARIMA model, the future value of a variable is supposed to be a linear combination of past values and past errors, expressed as follows…”
Section: Growth Analysis and Prediction Of Communities Using Arimamentioning
confidence: 99%
“…One of the most important and widely used time series models is the autoregressive integrated moving average (ARIMA) model Introduced by Box and Jenkins. ARIMA model is a traditional time series forecasting method and applied in various fields [35][36]. In an ARIMA model, the future value of a variable is supposed to be a linear combination of past values and past errors, expressed as follows…”
Section: Growth Analysis and Prediction Of Communities Using Arimamentioning
confidence: 99%
“…The Granger causality test describes the dynamic correlation among variables and does not indicate true causal relationships [44], but the recognized patterns present in the water-quality data enable an effective forecast. Classic prediction models employed in a wide array of water-quality studies include the Autoregressive Moving Average (ARMA) and the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) [45]. Vector Autoregression (VAR) is the other statistical model used in time-series forecasting.…”
Section: Introductionmentioning
confidence: 99%