Bagci, MuhiddinAltintas, Gokhan2015-04-012015-04-012007Journal of Science and Technology 1 (1), 2007, 43-571307-3818In this study, infilled planar frames and confined reinforced concrete section have been analysed using Artificial Neural Network (ANN). ANN architecture was chosen in which multi layer, feed forward, and back propagation algorithm was used. The training data of infill frame used were provided by a finite element model in which non-linearity of materials and the structural interface were taken into account under increasing lateral load. Using the proposed analytical model (layered model) were generated the training data for confined reinforced concrete section. Analytical technique uses realistic material models for confined and unconfined concrete. After completing the training phase, verification of the performance of the network was carried out using old (included in training phase) and new (not included in training phase) patterns. The controls conducted in the test phase. The findings of this exercise show that the ANN algorithm can be successfully and easily used within reasonable accuracy in order to decrease computational time in finding infill frame and the moment-curvature relationships of reinforced concrete sections.enArtificial Neural NetworkFinite Elements MethodInfilled FrameConfined Reinforced Concrete SectionMoment-CurvatureArticle