An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups

By Mohammad Mohammadhassani, Hossein Nezamabadi-pour, M. Suhatril, Mahdi Shariati. 2014

145 citations recorded by the source corpus.

Subfields: Building and Construction, Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/4707cb73d84eb8fe8809629c9748a49fd6773011

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. Trung Nguyen-Thoi
2. Masoud Ahmadi
3. A. Shariati
4. Mahdi Shariati

In Civil and Structural Engineering

1. Trung Nguyen-Thoi
2. Masoud Ahmadi
3. A. Shariati
4. Mahdi Shariati
5. Hung Nguyen-Xuan

Citations in the corpus

• A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement (2020, background): “This approach causes that ELM has the following advantages over the other proposed models [60, 65, 71]:”