Khajeh, Atieh, Mousavi, Seyed Roohollah, Rakhshani Mehr, Mehrollah. (1393). Adaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams. هنرهای کاربردی, 3(1), 14-23. doi: 10.22075/jrce.2015.355
Atieh Khajeh; Seyed Roohollah Mousavi; Mehrollah Rakhshani Mehr. "Adaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams". هنرهای کاربردی, 3, 1, 1393, 14-23. doi: 10.22075/jrce.2015.355
Khajeh, Atieh, Mousavi, Seyed Roohollah, Rakhshani Mehr, Mehrollah. (1393). 'Adaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams', هنرهای کاربردی, 3(1), pp. 14-23. doi: 10.22075/jrce.2015.355
Khajeh, Atieh, Mousavi, Seyed Roohollah, Rakhshani Mehr, Mehrollah. Adaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams. هنرهای کاربردی, 1393; 3(1): 14-23. doi: 10.22075/jrce.2015.355

Adaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams

Journal of Rehabilitation in Civil Engineering
مقاله 2، دوره 3، شماره 1 - شماره پیاپی 5، اردیبهشت 2015، صفحه 14-23    اصل مقاله (658.19 K)
نوع مقاله: Regular Paper
شناسه دیجیتال (DOI): 10.22075/jrce.2015.355
نویسندگان
Atieh Khajeh1؛ Seyed Roohollah Mousavi* 2؛ Mehrollah Rakhshani Mehr3
1M.S student, Department of Civil Engineering, University of Sistan and Baluchestan, zahedan, Iran
2Assistant Professor, Department of Civil Engineering, University of Sistan and Baluchestan, zahedan, Iran
3Assistant Professor, Department of Civil Engineering, University of Alzahra, Tehran, Iran
چکیده
A reinforced concrete member in which the total span or shear span is especially small in relation to its depth is called a deep beam. In this study, a new approach based on the Adaptive Neural Fuzzy Inference System (ANFIS) is used to predict the shear strength of reinforced concrete (RC) deep beams. A constitutive relationship was obtained correlating the ultimate load with seven mechanical and geometrical parameters. These parameters contain Web width, Effective depth, Shear span to depth ratio, Concrete compressive strength, Main reinforcement ratio, Horizontal shear reinforcement ratio and Vertical shear reinforcement ratio.
The ANFIS model is developed based on 214 experimental database obtained from the literature. The data used in the present study, out of the total data, 80% was used for training the model and 20% for checking to validate the model. The results indicated that ANFIS is an effective method for predicting the shear strength of reinforced concrete (RC) deep beams and has better accuracy and simplicity compared to the empirical methods.
کلیدواژه‌ها
Shear strength؛ RC deep beams؛ Adaptive Neural Fuzzy Inference System (ANFIS)
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