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Dergiler / Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering / 2023 / Volume: 65 Issue: 2

An optimized artificial neural network for estimating design effort of jigs and fixtures used in aviation industry

Umut Nazmi Aktan(Turkish Aerospace Company)0000-0002-6410-5720
Mehmet Dikmen(BASKENT UNIVERSITY)0000-0002-0584-5577
Sayfa
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Yayın Tarihi
2023-12-29
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The results showed that an optimized Artificial Neural Network architecture with binary encoding applied to the input data can be applied satisfactorily in the aviation industry for the solution of the given problem.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This paper investigates the usefulness of the machine learning methods to predict the design effort of jigs and fixtures used in the aviation industry.
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Temel Bulgular & Veri:Reaching the best possible result by determining the ideal machine learning model to obtain the best estimate and the most appropriate set of inputs and parameters forms the basis of this study.
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Sonuç & Katkı:The results showed that an optimized Artificial Neural Network architecture with binary encoding applied to the input data can be applied satisfactorily in the aviation industry for the solution of the given problem.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Tool design effort · aviation industry · artificial neural network

Abstract

This paper investigates the usefulness of the machine learning methods to predict the design effort of jigs and fixtures used in the aviation industry. Reaching the best possible result by determining the ideal machine learning model to obtain the best estimate and the most appropriate set of inputs and parameters forms the basis of this study. To that end, most popular machine learning models that can be used for regression are combined with various data encoding methods. The best combination is optimized as well. The results showed that an optimized Artificial Neural Network architecture with binary encoding applied to the input data can be applied satisfactorily in the aviation industry for the solution of the given problem.

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Bu Makaleye Atıf Yap

Aktan, U. N., Dikmen, M. (2023). An optimized artificial neural network for estimating design effort of jigs and fixtures used in aviation industry. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Volume: 65 Issue: 2. https://doi.org/10.33769/aupse.1254312

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Kaynakça (15)

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