The neural network approximation to the size effect in fracture of cementitious materials
ENGINEERING FRACTURE MECHANICS, cilt.54, sa.2, ss.249-261, 1996 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 54 Sayı: 2
- Basım Tarihi: 1996
- Doi Numarası: 10.1016/0013-7944(95)00140-9
- Dergi Adı: ENGINEERING FRACTURE MECHANICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.249-261
- Gazi Üniversitesi Adresli: Hayır
Özet
Modeling of material behavior generally involves the development of a mathematical model derived from observations and experimental data. An alternative way discussed in this paper, is neural network-based modeling that is a subfield of artificial intelligence. The main benefit in using a neural network approach is that the network is built directly from experimental data using the self-organising capabilities of the neural network. In this paper, size effects in fracture of cementitious materials are modeled with a back-propagation neural network. The results of neural network-based size effect law look viable and very promising. Copyright (C) 1996 Elsevier Science Ltd.