Shear connectors in composite floor systems play an important role in the seismic response of a structure. The prediction of shear capacity of these shear connectors is very difficult. The conventional push-out tests and simple modelling of these connectors provide limited guidance in their structural behavior and the results are valid only for the selected testing protocol. Recent advancements in the area of Artificial Intelligence (AI) have made it feasible to utilize the application of these technologies in the construction industry and structural analysis. This book aims at predicting the shear strength of shear connectors in composite beam comprised of steel and concrete sections using ANFIS as a non-linear modelling tool and the classical Linear Regression (LR) as a linear modelling tool. ANFIS produces highly accurate, precise and satisfactory results as compared to LR. Afterwards, ANFIS network was used to determine which parameters are the most influential on shear strength of shear connectors. Variable searching using the ANFIS network was also performed to determine how the selected parameters affect the shear strength.

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Ali Toghroli was born in Baft, Iran in 1986. He earned his bachelor's degree in civil engineering in IAU of Kerman, Iran and his master degree in construction management engineering from the IAU of Tehran.He is performing his PhD in construction technology and management.