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Unmanned Ground Vehicle Selection with Artificial Neural Networks     
Yazarlar (3)
Öğr. Gör. Cüneyd DEMİR Öğr. Gör. Cüneyd DEMİR
Kırşehir Ahi Evran Üniversitesi, Türkiye
Cengiz Eldem
Gazi Üniversitesi, Türkiye
Mustafa Bozdemir
Kırıkkale Üniversitesi, Türkiye
Devamını Göster
Özet
In recent years, significant advancements have been made in defense systems in response to the increasing demands of countries. The importance of unmanned ground vehicles, a highly critical technology, is becoming more evident with each passing year. In this study, a selection program is intended to be developed to determine the mission purposes for which military unmanned ground vehicles will be used. In line with the operating principles, the basic mechanical systems have been identified. Subsequently, a design catalog containing these basic mechanical systems was created. The desired features for use in the field were asked to the customer. Based on the received responses, the best alternative unmanned ground vehicles were identified using an artificial neural network algorithm. In the artificial neural network model, a feedforward neural network architecture was used. Stochastic Gradient Descent was utilized in the network training function to minimize the model's loss function. The activation functions tanh and softmax were used, and the model has four hidden layers. The model was trained for 150 epochs. Results were obtained for the metrics of accuracy, precision, recall, and F1-score. The model's accuracy rate was found to be %99,63. Such a high accuracy rate indicates that the model has well understood the data in the dataset and provides accurate predictions.
Anahtar Kelimeler
Makale Türü Özgün Makale
Makale Alt Türü Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayımlanan tam makale
Dergi Adı International Journal of 3D Printing Technologies and Digital Industry
Dergi ISSN 2602-3350
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili Türkçe
Basım Tarihi 01-2024
Cilt No 8
Sayı 2
Sayfalar 255 / 265
Doi Numarası 10.46519/ij3dptdi.1482087
Makale Linki http://dx.doi.org/10.46519/ij3dptdi.1482087
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Unmanned Ground Vehicle Selection with Artificial Neural Networks

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