Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II: beams with stirrups

By Antoni Cladera, A. Marí. 2004

204 citations recorded by the source corpus.

Subfields: Building and Construction, Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/b71f5be3d6d6c442eaa3ffbd8a55968cfe8f2a6a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. A. Marí
2. Antoni Cladera
3. Panagiotis G. Asteris

In Civil and Structural Engineering

1. A. Marí
2. Antoni Cladera
3. K. Roinos
4. Maria G. Douvika
5. Konstantinos G. Kolovos
6. Panagiotis G. Asteris
7. J. Bairán

Citations in the corpus

• Prediction of self-compacting concrete strength using artificial neural networks (2016, background): “…mainly publications concerning the application of ANNs for the prediction of the compressive strength and modulus of elasticity (Atici, 2011; Cladera & Marí, 2004; Dias & Pooliyadda, 2001; González-Taboada, GonzálezFonteboa, Martínez-Abella, & Pérez-Ordóñez, 2016; Kostić & Vasović, 2015;…”
• Shear-flexural strength mechanical model for the design and assessment of reinforced concrete beams subjected to point or distributed loads (2014, background): “that vc depends also on the shear carried by the transverse reinforcement, vs, as was observed experimentally [14,26].”