[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 11, Issue 36 (4-2017) ::
jwmseir 2017, 11(36): 33-42 Back to browse issues page
Bayesian networks, Gamma Test, Groundwater level, model Least Squares Support Vector Machine, Plain Ardebil
Fateme Akhoni pourhosseini * , Esmaeel Asadi
Abstract:   (7737 Views)

Groundwater has been raised as one of the major sources of water supply for drinking and agriculture, especially in arid and semi-arid. Simulation of groundwater system because of the complexity of these systems is a difficult task. In this paper, using data Ardabil plain water level in the period (1972-2011), the evaluation and selection of appropriate inputs for processing gamma test performance and efficiency of the least squares support vector machines and Bayesian network models were discussed. Monthly water level as input parameters with different delays Gamma test was considered. Gamma test results showed that the water level by 6 latency, offers better results to predict. Water level simulation using least squares support vector machines and Bayesian network models also showed that the input structure to predict the water level the next month will be delayed until six. The two models with the same input structure, least squares support vector machine model, better performance, according to the coefficient of determination 0.977, mean absolute error 0.204 and root mean square error 0.307, compared to Bayesian networks have. The results showed that gamma test compound in the appropriate input soft computing can have a better performance.

Keywords: Bayesian networks, Gamma Test, Groundwater level, Plain Ardebil, Support Vector Machine
Full-Text [PDF 887 kb]   (5598 Downloads)    
Type of Study: case report | Subject: Special
Received: 2016/02/9 | Accepted: 2016/11/21 | Published: 2017/03/14
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

akhoni pourhosseini F, asadi E. Bayesian networks, Gamma Test, Groundwater level, model Least Squares Support Vector Machine, Plain Ardebil. jwmseir 2017; 11 (36) :33-42
URL: http://jwmsei.ir/article-1-597-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 11, Issue 36 (4-2017) Back to browse issues page
مجله علوم ومهندسی آبخیزداری ایران Iranian Journal of Watershed Management Science and Engineering
Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4645