COMPARISON OF ANN, ANFIS AND REGRESSION MODELS TO ESTIMATE GROUNDWATER LEVEL OF NEYSHABOOR AQUIFER

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.

KHASHEI SIUKI A.; GHAHRAMAN B.; KOUCHAKZADEH M.

Educational Videos and Scientific Workshops

Scientific Information Database

ISSN: 2588-4824

Journal Paper

Paper Information

Journal: Iranian Journal of Irrigation and Drainage Year:2013 | Volume:7 | Issue:1 Page(s): 10-22

Download Full-Text

Persian Verion

View:

868

Download:

Cites:

Information Journal Paper

Title

COMPARISON OF ANN, ANFIS AND REGRESSION MODELS TO ESTIMATE GROUNDWATER LEVEL OF NEYSHABOOR AQUIFER

Author(s)

KHASHEI SIUKI A. | GHAHRAMAN B. | KOUCHAKZADEH M. | Issue Writer Certificate

Keywords

GROUNDWATERQ2

GISQ2

NEYSHABUR PLAINQ2

MULTIVARIABLE REGRESSION MODELQ2

EXPERT SYSTEMQ1

Abstract

GROUNDWATER and water resources management play a key role in sustainable water resources management in arid and semi-arid areas. Neyshaboor plain is one of the most plains of Khorasan Razavi province, which has an important role in agricultural production. Unallowable discharges of the resources is causing that water table has 74 cm drawdown. Purpose of this study is evaluated of classic models and EXPERT SYSTEMs (Artificial Neural Network ANN and Adaptive Neurao-Fuzzy Inference Systems ANFIS) in prediction of GROUNDWATER table. In this study, effected parameters in water table example (monthly precipitation and discharge) detected and raster maps was gained by geostatistical methods. Data bank was gained by Arc GIS software from raster maps to training and testing EXPERT SYSTEMs. Regression equations of effective parameters in water table were resulted from data bank. Results showed that ANFIS models often had the most accuracy to predict monthly and regression models had the lowest performance. The ANN models had suitable accuracy on summery months.

Cites

No record.

References

No record.

Cite

APA: Copy

KHASHEI SIUKI, A., GHAHRAMAN, B., & KOUCHAKZADEH, M.. (2013). COMPARISON OF ANN, ANFIS AND REGRESSION MODELS TO ESTIMATE GROUNDWATER LEVEL OF NEYSHABOOR AQUIFER. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, 7(1), 10-22. SID. https://sid.ir/paper/131643/en

Vancouver: Copy

KHASHEI SIUKI A., GHAHRAMAN B., KOUCHAKZADEH M.. COMPARISON OF ANN, ANFIS AND REGRESSION MODELS TO ESTIMATE GROUNDWATER LEVEL OF NEYSHABOOR AQUIFER. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE[Internet]. 2013;7(1):10-22. Available from: https://sid.ir/paper/131643/en

IEEE: Copy

A. KHASHEI SIUKI, B. GHAHRAMAN, and M. KOUCHAKZADEH, “COMPARISON OF ANN, ANFIS AND REGRESSION MODELS TO ESTIMATE GROUNDWATER LEVEL OF NEYSHABOOR AQUIFER,” IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, vol. 7, no. 1, pp. 10–22, 2013, [Online]. Available: https://sid.ir/paper/131643/en

Related Journal Papers

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops

Download

Move to top

وبگردی