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Abstract
The main objective of this research is to develop an artificial Neural Network that is able to predict shear strength for fiber reinforced concrete beams because of difficulty of it and simplify its use through developing a Graphic User Interface (GUI). Moreover, shear behavior in fiber reinforced concrete beams (FRCBs) is quantified by compressive strength of concrete, longitudinal steel, size effect, fiber’s type, content and aspect ratio. The research methodology is based on collecting experimental results of technical investigations carried out so as to predict shear behavior in FRCBs. For this, two back-propagation neural networks have been experimented by MATLAB; their types have been fitting (1st network) and pattern recognition (2nd network) which have been used to classify failure of FRC beams into 6 categories. The training algorithms use feed forward back propagation. The ANNs model has been assessed in comparison with exact values and deduces a good correlation with it