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Dergiler / Electrica / 2018 / Cilt: 18 - Sayı: 1

An Analysis of the Effects of SVM Parameters on the Dead-Time System Modeling

NİHAT KABAOĞLU
Rana ORTAÇ KABAOĞLU
Sayfa
1–5
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The performance of the method proposed herein was examined with different parameters in linear and nonlinear dead-time systems.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Modeling a dead-time system is a common issue in engineering applications.
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Temel Bulgular & Veri:To address this issue, existing research has employed neural networks and fuzzy logic-based intelligent systems.
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Sonuç & Katkı:The performance of the method proposed herein was examined with different parameters in linear and nonlinear dead-time systems.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Özet

Modeling a dead-time system is a common issue in engineering applications. To address this issue, existing research has employed neural networks and fuzzy logic-based intelligent systems. Herein, a dead-time system modeled with the aid of support vector machine regression, which has a good generalization feature, was investigated. The performance of the method proposed herein was examined with different parameters in linear and nonlinear dead-time systems.

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Bu Makaleye Atıf Yap

KABAOĞLU, N., KABAOĞLU, R. O. (2018). An Analysis of the Effects of SVM Parameters on the Dead-Time System Modeling. Electrica, Cilt: 18 - Sayı: 1, 1–5. https://ajindex.com/articles/153724

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Kaynakça (7)

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