Research Article

Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate

Volume: 8 Number: 1 January 19, 2024
EN

Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate

Abstract

Since we all have our own set of limitations when it comes to perceiving the world and reasoning profoundly, we are constantly met with uncertainty as a result of a lack of information (lexical impression, incompleteness), as well as specific measurement inaccuracies. It has been found that uncertainty, which shows up as ambiguity, is the root cause of complexity, which is everywhere in the real world. Most of the uncertainty in civil engineering systems comes from the fact that the constraints (parameters) are hard to understand and are described in a vague way. The ambiguity comes from a number of sources, including physical arbitrariness, statistical uncertainty due to using limited information to estimate these characteristics, and model uncertainty due to using overly simplified methods and idealized depictions of actual performances. Thus, it is better to combine fuzzy set theory and fuzzy logic. Fuzzy logic is well-suited to modelling the indeterminacy and ambiguity that results from multiple factors and a lack of data. In order to improve upon a previous predictive model, this paper uses a smart model built on a fuzzy logic system (FLS). Precipitation, temperature, humidity, slope, and land use data were all taken into account as input variables in the fuzzy model. Toprak's original explanation of the simple membership function and fuzzy rules generation technique (SMRGT) was based on the fuzzy-Mamdani methodology and used the flow coefficient as its output. The model's results were compared to available data. The following factors were considered in the comparison: 1) The maximum, minimum, mean, standard deviation, skewness, variation, and correlation coefficients are the seven statistical parameters. 2) Four types of error criteria: Mean Absolute Relative Error (MARE), Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). 3) Scatter diagram.

Keywords

References

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Early Pub Date

September 15, 2023

Publication Date

January 19, 2024

Submission Date

December 28, 2022

Acceptance Date

March 10, 2023

Published in Issue

Year 2024 Volume: 8 Number: 1

APA
Günal, A. Y., & Mehdi, R. (2024). Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate. Turkish Journal of Engineering, 8(1), 46-55. https://doi.org/10.31127/tuje.1225795
AMA
1.Günal AY, Mehdi R. Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate. TUJE. 2024;8(1):46-55. doi:10.31127/tuje.1225795
Chicago
Günal, Ayşe Yeter, and Ruya Mehdi. 2024. “Application of a New Fuzzy Logic Model Known As ‘SMRGT’ for Estimating Flow Coefficient Rate”. Turkish Journal of Engineering 8 (1): 46-55. https://doi.org/10.31127/tuje.1225795.
EndNote
Günal AY, Mehdi R (January 1, 2024) Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate. Turkish Journal of Engineering 8 1 46–55.
IEEE
[1]A. Y. Günal and R. Mehdi, “Application of a new fuzzy logic model known as ‘SMRGT’ for estimating flow coefficient rate”, TUJE, vol. 8, no. 1, pp. 46–55, Jan. 2024, doi: 10.31127/tuje.1225795.
ISNAD
Günal, Ayşe Yeter - Mehdi, Ruya. “Application of a New Fuzzy Logic Model Known As ‘SMRGT’ for Estimating Flow Coefficient Rate”. Turkish Journal of Engineering 8/1 (January 1, 2024): 46-55. https://doi.org/10.31127/tuje.1225795.
JAMA
1.Günal AY, Mehdi R. Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate. TUJE. 2024;8:46–55.
MLA
Günal, Ayşe Yeter, and Ruya Mehdi. “Application of a New Fuzzy Logic Model Known As ‘SMRGT’ for Estimating Flow Coefficient Rate”. Turkish Journal of Engineering, vol. 8, no. 1, Jan. 2024, pp. 46-55, doi:10.31127/tuje.1225795.
Vancouver
1.Ayşe Yeter Günal, Ruya Mehdi. Application of a new fuzzy logic model known as "SMRGT" for estimating flow coefficient rate. TUJE. 2024 Jan. 1;8(1):46-55. doi:10.31127/tuje.1225795

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