OPTIMIZING ANFIS FOR SEDIMENT TRANSPORT IN OPEN CHANNELS USING DIFFERENT EVOLUTIONARY ALGORITHMS

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.

QASEM SULTAN NOMAN; EBTEHAJ ISA; RIAHI MADAVAR HOSSIEN

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

Journal Paper

Paper Information

Journal: JOURNAL OF APPLIED RESEARCH IN WATER AND WASTEWATER Year:2017 | Volume:4 | Issue:1 Page(s): 290-298

Download Full-Text

View:

262

Download:

152

Cites:

Information Journal Paper

Title

OPTIMIZING ANFIS FOR SEDIMENT TRANSPORT IN OPEN CHANNELS USING DIFFERENT EVOLUTIONARY ALGORITHMS

Author(s)

QASEM SULTAN NOMAN | EBTEHAJ ISA | RIAHI MADAVAR HOSSIEN | Issue Writer Certificate

Keywords

ANFIS

DIFFERENTIAL EVOLUTION (DE)

GENETIC ALGORITHM (GA)

NON-DEPOSITION SEDIMENT TRANSPORT

PARTICLE SWARM OPTIMIZATION (PSO)

Abstract

Flow through open channels can contain solids. The deposition of solids occasionally occurs due to insufficient flow velocity to transfer the solid particles, causing many problems with transfer systems. Therefore, a method to determine the limiting velocity (i.e. Fr) is required. In this paper, three alternative, hybrid evolutionary algorithm methods, including differential evolution (DE), genetic algorithm (GA) and particle swarm optimization (PSO) based on the adaptive network-based fuzzy inference system are presented: ANFIS-GA, ANFIS-DE and ANFIS-PSO. In these methods, evolutionary algorithms optimize the membership functions, and ANFIS adjusts the premises and consequent parameters to optimize prediction performance. The performance of the proposed methods is compared with that of the general ANFIS using three different datasets comprising a wide range of data. The results show that the hybrid models (ANFIS-GA, ANFIS-DE and ANFIS-PSO) are more accurate than general ANFIS in training with a hybrid algorithm (hybrid of back propagation and least squares). Among the evolutionary algorithms, ANFIS-PSO performed the best (R2=0.976, RMSE=0.26, MARE=0.057, BIAS=-0.004 and SI=0.059).

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

QASEM, SULTAN NOMAN, EBTEHAJ, ISA, & RIAHI MADAVAR, HOSSIEN. (2017). OPTIMIZING ANFIS FOR SEDIMENT TRANSPORT IN OPEN CHANNELS USING DIFFERENT EVOLUTIONARY ALGORITHMS. JOURNAL OF APPLIED RESEARCH IN WATER AND WASTEWATER, 4(1), 290-298. SID. https://sid.ir/paper/352864/en

Vancouver: Copy

QASEM SULTAN NOMAN, EBTEHAJ ISA, RIAHI MADAVAR HOSSIEN. OPTIMIZING ANFIS FOR SEDIMENT TRANSPORT IN OPEN CHANNELS USING DIFFERENT EVOLUTIONARY ALGORITHMS. JOURNAL OF APPLIED RESEARCH IN WATER AND WASTEWATER[Internet]. 2017;4(1):290-298. Available from: https://sid.ir/paper/352864/en

IEEE: Copy

SULTAN NOMAN QASEM, ISA EBTEHAJ, and HOSSIEN RIAHI MADAVAR, “OPTIMIZING ANFIS FOR SEDIMENT TRANSPORT IN OPEN CHANNELS USING DIFFERENT EVOLUTIONARY ALGORITHMS,” JOURNAL OF APPLIED RESEARCH IN WATER AND WASTEWATER, vol. 4, no. 1, pp. 290–298, 2017, [Online]. Available: https://sid.ir/paper/352864/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops