EN
Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes
Abstract
Parabolic blending (PB) is one of the important topics in applied mathematics and computer graphics. The use of generalized parabolic blending (GPB) for different scenarios adds flexibility to the polynomial. Overhauser (OVR) elements is a special case in GPB (r=0.5, s=0.5). GPB can also be used in estimation. In this study, data obtained from thickness distribution of a 3mm thick high impact polystyrene product after thermoforming using a mold was used for data estimation. For this purpose, software has been developed. The software development steps and formula usages are explained. Using the developed software, polynomials for GPB and default PB (OVR) were created. The data set was compared with the y values produced by the polynomials for certain x values. At the end of the research, it was determined that the results obtained from the GPB were 0.1728 percent more accurate than the data obtained from the PB for the default values.
Keywords
References
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Details
Primary Language
English
Subjects
Software Engineering , Software Testing, Verification and Validation , Software Engineering (Other)
Journal Section
Research Article
Authors
Hakan Üstünel
*
0000-0001-9903-593X
Türkiye
Publication Date
December 31, 2022
Submission Date
May 27, 2022
Acceptance Date
November 18, 2022
Published in Issue
Year 1970 Volume: 5 Number: 3
APA
Üstünel, H. (2022). Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. Sakarya University Journal of Computer and Information Sciences, 5(3), 356-370. https://doi.org/10.35377/saucis...1122506
AMA
1.Üstünel H. Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. SAUCIS. 2022;5(3):356-370. doi:10.35377/saucis.1122506
Chicago
Üstünel, Hakan. 2022. “Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes”. Sakarya University Journal of Computer and Information Sciences 5 (3): 356-70. https://doi.org/10.35377/saucis. 1122506.
EndNote
Üstünel H (December 1, 2022) Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. Sakarya University Journal of Computer and Information Sciences 5 3 356–370.
IEEE
[1]H. Üstünel, “Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes”, SAUCIS, vol. 5, no. 3, pp. 356–370, Dec. 2022, doi: 10.35377/saucis...1122506.
ISNAD
Üstünel, Hakan. “Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes”. Sakarya University Journal of Computer and Information Sciences 5/3 (December 1, 2022): 356-370. https://doi.org/10.35377/saucis. 1122506.
JAMA
1.Üstünel H. Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. SAUCIS. 2022;5:356–370.
MLA
Üstünel, Hakan. “Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 3, Dec. 2022, pp. 356-70, doi:10.35377/saucis. 1122506.
Vancouver
1.Hakan Üstünel. Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. SAUCIS. 2022 Dec. 1;5(3):356-70. doi:10.35377/saucis. 1122506
