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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