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Traditional analysis methods used in Structural Engineering are reliable and can be successfully applied by solving several numerical equations. Another alternative analytical modeling method is Artificial Neural Networks (ANNs), which capture the numerical equations between its nodes and no formal formula is observable within the network generation. ANN system is an acceptable method in predicting experimental results. In this book, FBNN and GRNN are generated to predict the load-deflection analysis in the one-way non-strengthened and Carbon Fiber Reinforced Polymer (CFRP) strengthened RC slab. The GRNN was applied for situation where training data is insufficient for network generation. In addition, GRNN is also applied for the mechanical strength prediction of lightweight concrete and mortar.

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Dr. Seyed Vahid Razavi tosee is a holder of academic position in Structural Engineering Department 0f Joundi-shapor University of Technology, Dezful, Iran. His main areas of research includes Structural Engineering, Neural Networks, Smart Structures, Structural dynamics, and more recently dynamic assessment and health monitoring of bridges.

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