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Dergiler / Sakarya University Journal of Computer and Information Sciences / 2022 / Volume: 5 Issue: 3

Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes

Hakan Üstünel(KIRKLARELI UNIVERSITY)0000-0001-9903-593X
Sayfa
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Yayın Tarihi
2022-12-31
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Parabolic blending (PB) is one of the important topics in applied mathematics and computer graphics.
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Temel Bulgular & Veri:Overhauser (OVR) elements is a special case in GPB (r=0.5, s=0.5).
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Sonuç & Katkı: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.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Generalized parabolic blending · computer graphics · visualization

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.

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Bu Makaleye Atıf Yap

Üstünel, H. (2022). Software Development for the Use of Generalized Parabolic Blending in Data Prediction Processes. Sakarya University Journal of Computer and Information Sciences, Volume: 5 Issue: 3. https://doi.org/10.35377/saucis...1122506

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