Case–Based Approaches for Preliminary Design of Steel Building Frames

Case-based reasoning (CBR) is a technique for solving new problems by adapting solutions that were obtained by solving old problems. In this article, three distinct CBR methodologies are examined for their efficiency and accuracy in modeling steel building frame design, including conventional nearest neighbor CBR and two novel CBR methodologies, collaborative CBR, which combines several cases to generate a better solution, and hybrid CBR, which hybridizes two important CBR mechanisms, adaptation and combination, to obtain a more accurate solution. The results show that the hybrid CBR techniques are slightly more accurate than back-propagation neural networks and much more accurate than the other two CBR methodologies.