OICC Press Journal of Solid Mechanics 2008-7683 17 4 2025 12 31 Predicting One-Way slabs' Shear Capacity Subjected to Concentrated Loading Using ANN-Based Formulation 10.57647/jsm.2025.1704.17 EN Ali Asghar Akbari Bargoshadi Department of Civil Engineering, Ur.C., Islamic Azad University, Urmia, Iran Ashkan Khodabandehlou Department of Civil Engineering, Ur.C., Islamic Azad University, Urmia, Iran https://orcid.org/0009-0004-2675-0069 Fedra Ashrafzadeh Department of Civil Engineering, Ur.C., Islamic Azad University, Urmia, Iran Peyman Hamidi Journal Article 2025 12 31 The main goal of this study is to present a neural network-based relationship to predict the shear capacity of one-way slabs under concentrated loads. For this purpose, after modeling 5 one-way slabs with different dimension ratios (between 2 and 3.33) by ETABS, the shear capacity of the slab for applying concentrated load along the long span (for eleven different positions) was calculated and the maximum deflection created in the slab was compared and controlled with the allowed value of the codes. After training the optimized neural network, using data obtained from ETABS, the shear capacity of slabs was predicted by MATLAB and the accuracy of this prediction was checked using the regression coefficient. Then, using data fitting and linear regression, the general equation for bearing capacity of the concrete slab in terms of the location of the concentrated load (α) was determined. Finally, in order to determine the accuracy of the presented equation, the real shear capacity of a one-way slab was calculated and compared with the numerical value obtained from the proposed equation. The obtained results indicate the acceptable accuracy of the proposed equation which could predict the shear capacity of the slabs by 96.39%.