مشخصات پژوهش

عنوان	A Pioneering Approach to Predicting the Shear Strength of RC Beams by Employing Artificial Intelligence Techniques
نوع پژوهش	مقاله چاپ‌شده
کلیدواژه‌ها	Artificial Intelligence (AI), Adaptive Neuro-Fuzzy Interface System (ANFIS), Artificial Neural Networks (ANNs), Shear Strength, RC Beams
چکیده	Shear failures exhibit a brittle nature, often resulting in catastrophic collapse without sufficient advance warning or the capacity to redistribute internal stresses. Consequently, shear failures pose a greater risk and require more attention from structural engineers. It is crucial to incorporate preventive measures in structural design to avoid abrupt shear failures. The work presented in this article attempts to predict the shear strength of reinforced concrete beams as a complex structural engineering problem without the need for extra computational resources by employing the capabilities of Artificial Intelligence (AI) techniques. In recent decades, significant amounts of research have been done on the AI methods such as artificial neural networks (ANNs), fuzzy logic and genetic algorithms to predict the shear strength of RC beams. In this research, adaptive neuro-fuzzy inference system (ANFIS) and ANNs are developed to predict the shear capacity of RC beams.
پژوهشگران	مسعود پاکنهاد (نفر پنجم)، محمد محمد حسنی (نفر چهارم)، وان ابراهیم (نفر سوم)، اکرم مهیا (نفر دوم)، سید جمال سید حکیم (نفر اول)