WATER TABLE PREDICTION BY USE OF TIME SERIES MODELS AND ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM

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.

CHOUBIN BAHRAM; MALEKIAN ARASH; SAJEDI HOSSEINI FARZANEH; RAHMATI OMID

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

Journal Paper

Paper Information

Journal: Iranian Journal of Soil and Water Research Year:2014 | Volume:45 | Issue:1 Page(s): 19-28

Download Full-Text

Persian Verion

View:

729

Download:

Cites:

Information Journal Paper

Title

WATER TABLE PREDICTION BY USE OF TIME SERIES MODELS AND ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM

Author(s)

CHOUBIN BAHRAM | MALEKIAN ARASH | SAJEDI HOSSEINI FARZANEH | RAHMATI OMID | Issue Writer Certificate

Keywords

ANFISQ2

ARIMAQ1

GAMMA TESTQ2

TAYLOR DIAGRAMSQ1

Abstract

Modeling in arid regions to better manage water resources is a subject of paramount importance. Groundwater is a precious water resource especially in arid regions. The purpose followed in the present study was to assess the performance of Adaptive Neuro Fuzzy Inference System (ANFIS) and time series models in predicting the level of a water table. Throughout the study, groundwater levels in Shiraz plain were forecasted for one month beforehand by use of time series, and as well by ANFIS models. In the ANFIS model, Gamma and M-test were used to determine the optimal input combination and training as well as testing data length. Performance of different models was compared with reference to the parameters of error and TAYLOR DIAGRAMS. ANFIS model results indicated that this model with a Ȇ shaped membership function benefits from a more acceptable performance than the rest of the membership functions. A performance comparison of the models indicated a very suitable performance of the ARIMA (2, 1, 2) model in comparison with ANFIS different membership functions.

Cites

No record.

References

No record.

Cite

APA: Copy

CHOUBIN, BAHRAM, MALEKIAN, ARASH, SAJEDI HOSSEINI, FARZANEH, & RAHMATI, OMID. (2014). WATER TABLE PREDICTION BY USE OF TIME SERIES MODELS AND ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, 45(1), 19-28. SID. https://sid.ir/paper/225952/en

Vancouver: Copy

CHOUBIN BAHRAM, MALEKIAN ARASH, SAJEDI HOSSEINI FARZANEH, RAHMATI OMID. WATER TABLE PREDICTION BY USE OF TIME SERIES MODELS AND ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH[Internet]. 2014;45(1):19-28. Available from: https://sid.ir/paper/225952/en

IEEE: Copy

BAHRAM CHOUBIN, ARASH MALEKIAN, FARZANEH SAJEDI HOSSEINI, and OMID RAHMATI, “WATER TABLE PREDICTION BY USE OF TIME SERIES MODELS AND ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM,” IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, vol. 45, no. 1, pp. 19–28, 2014, [Online]. Available: https://sid.ir/paper/225952/en

Related Journal Papers