Prediksi Tebal Lapisan Beraspal Menggunakan Data Lendutan FWD dan Metoda Neural Network Untuk Single Layer Perception  

Oleh:

Siegfried

Jenis: Article from Journal - ilmiah nasional - tidak terakreditasi DIKTI
Dalam koleksi: Jurnal Jalan-Jembatan vol. 26 no. 1 (Apr. 2009), page 1-11.
Topik: Jaringan Syaraf; Single Layer Perceptron; Lendutan; FWD

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: JJ9.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

At the time the use of non destructive test for pavement has been a trend because of its effectiveness and mobility. Falling Weight deflectometer (FWD) is famous equipment for this aim. Actually the use of FWD is to collect structural data in term of deflection. The deflection data also can be used to predict the thickness of bituminous layer using the neural network of single layer perception. For three locations tested it is found that the difference between the thickness obtained from test pit and the average result using this neural network calculation is less than 10%. It is recommended that this method can be considered to use for collecting pavement data especially for building a data base.

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