Evaluation of genetic expression programming model for suspended sediment load estimation based on data preprocessing using gamma test method (case study: Rood Zard Watershed)

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.

Alijanpour Shalmani Adele; VAEZI ALIREZA; TABATABAEI MAHMOODREZA

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

Journal Paper

Paper Information

Journal: JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION Year:2019 | Volume:8 | Issue:4 Page(s): 37-49

Download Full-Text

Persian Verion

View:

607

Download:

Cites:

Information Journal Paper

Title

Evaluation of genetic expression programming model for suspended sediment load estimation based on data preprocessing using gamma test method (case study: Rood Zard Watershed)

Author(s)

Alijanpour Shalmani Adele | VAEZI ALIREZA | TABATABAEI MAHMOODREZA | Issue Writer Certificate

Keywords

Gamma testQ1

Genetic Expression ProgrammingQ2

SedimentQ1

WatershedQ2

Abstract

One of the effective factors to identify the problems of Watersheds is the daily suspended Sediment load. Due to the lack of sufficient data in direct measurement of daily suspended Sediment, intelligent models like the Genetic Expression Programing model (GEP) can be used to estimate it. In this research, the data of the machine hydrometric station was used in the Rood Zard Watershed with a statistical period of 36 years (1977-2012). The input variables of the GEP model include instantaneous flow discharge (Q), average daily flow discharge (Qi) and average daily precipitation (Pi) with three steps of time delay and output variable to the model includes daily suspended Sediment load. In order to reduce time and cost, pre-processing of input data into the GEP model was obtained using Gamma test method and entered the GEP model along with non-preprocessing combinations of the test and error method. The results of comparison between all models showed that the best combination of input variable from Gamma test with the lowest standard error is zero, gamma statistic is 0. 000092 and Vratio statistic is 0. 012 and the combination of variables including average daily flow discharge with two steps of time delay and average daily precipitation with three steps of time delay, had the most accurate and correct estimate for suspended Sediment load. This model had the lowest value of RMSE=1671. 90 (ton/day) and MAE=475. 68 (ton/day) and the highest value of R2=0. 99 and NSE=0. 99 compared to other models. Therefore, the use of Gamma test method as a data preprocessing method, by selecting combinations of appropriate input variables to models, an average of up to 40% of the estimated error (RMSE) of daily suspended Sediment load compared to the inputs from the test and reduce the error and increase the performance of the GEP model in estimating the suspended Sediment load by increasing the similarity between the values of observational data with computational data.

Cites

No record.

References

No record.

Cite

APA: Copy

Alijanpour Shalmani, Adele, VAEZI, ALIREZA, & TABATABAEI, MAHMOODREZA. (2019). Evaluation of genetic expression programming model for suspended sediment load estimation based on data preprocessing using gamma test method (case study: Rood Zard Watershed). JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, 8(4 ), 37-49. SID. https://sid.ir/paper/232190/en

Vancouver: Copy

Alijanpour Shalmani Adele, VAEZI ALIREZA, TABATABAEI MAHMOODREZA. Evaluation of genetic expression programming model for suspended sediment load estimation based on data preprocessing using gamma test method (case study: Rood Zard Watershed). JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION[Internet]. 2019;8(4 ):37-49. Available from: https://sid.ir/paper/232190/en

IEEE: Copy

Adele Alijanpour Shalmani, ALIREZA VAEZI, and MAHMOODREZA TABATABAEI, “Evaluation of genetic expression programming model for suspended sediment load estimation based on data preprocessing using gamma test method (case study: Rood Zard Watershed),” JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, vol. 8, no. 4 , pp. 37–49, 2019, [Online]. Available: https://sid.ir/paper/232190/en

Related Journal Papers