A HYBRID MODEL FOR FORECASTING DAILY URBAN WATER DEMAND

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ARAM ABDOL RAHMAN; AGHELI LOTFALI

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Quantitative Economics Year:2012 | Volume:9 | Issue:1 (32) Page(s): 1-17

Download Full-Text

Persian Verion

View:

891

Download:

Cites:

Information Journal Paper

Title

A HYBRID MODEL FOR FORECASTING DAILY URBAN WATER DEMAND

Author(s)

ARAM ABDOL RAHMAN | AGHELI LOTFALI | Issue Writer Certificate

Keywords

FORECASTINGQ2

DEMANDQ2

URBAN WATERQ2

WAVELET TRANSFORMQ2

ARTIFICIAL NEURAL NETWORKSQ2

Abstract

Water as one of the most important human needs plays a vital role in everyday life. Therefore, awareness of the required amount of water DEMAND is of particular importance to policy-making in line with DEMAND management. In this study, a hybrid model (a combination of linear and non-linear models) has been designed to predict short-term URBAN WATER DEMAND which matches with the climatic conditions and structure of Tehran and variables affecting the water consumption. With using the model, daily URBAN WATER DEMAND for the next 10 days was predicted based by ARIMA, ARTIFICIAL NEURAL NETWORKS (ANN) and WAVELET TRANSFORM hybrid models. Then the forecasted values of mentioned models were evaluated by MAPE and R2 criteria in step-by-step and full 10 days predictions. Finally, WAVELET TRANSFORM hybrid model with low error (high prediction accuracy) was selected as an optimal model for predicting daily water DEMAND of Tehran.

Cites

No record.

References

Cite

APA: Copy

ARAM, ABDOL RAHMAN, & AGHELI, LOTFALI. (2012). A HYBRID MODEL FOR FORECASTING DAILY URBAN WATER DEMAND. JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW), 9(1 (32)), 1-17. SID. https://sid.ir/paper/110831/en

Vancouver: Copy

ARAM ABDOL RAHMAN, AGHELI LOTFALI. A HYBRID MODEL FOR FORECASTING DAILY URBAN WATER DEMAND. JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW)[Internet]. 2012;9(1 (32)):1-17. Available from: https://sid.ir/paper/110831/en

IEEE: Copy

ABDOL RAHMAN ARAM, and LOTFALI AGHELI, “A HYBRID MODEL FOR FORECASTING DAILY URBAN WATER DEMAND,” JOURNAL OF QUANTITATIVE ECONOMICS (QUARTERLY JOURNAL OF ECONOMICS REVIEW), vol. 9, no. 1 (32), pp. 1–17, 2012, [Online]. Available: https://sid.ir/paper/110831/en

Related Journal Papers