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Structural Monitoring and Maintenance
  Volume 5, Number 4, December 2018, pages 445-461

Assessing the ductility of moment frames utilizing genetic algorithm and artificial neural networks
Moosa Mazloom, Hossein Afkar and Pardis Pourhaji

    The aim of this research is to evaluate the effects of the number of spans, height of spans, number of floors, height of floors, column to beam moment of inertia ratio, and plastic joints distance of beams from columns on the ductility of moment frames. For the facility in controlling the ductility of the frames, this paper offers a simple relation instead of complex equations of different codes. For this purpose, 500 analyzed and designed frames were randomly selected, and their ductility was calculated by the use of nonlinear static analysis. The results cleared that the column-to-beam moment of inertia ratio had the highest effect on ductility, and if this relation was more than 2.8, there would be no need for using the complex relations of codes for controlling the ductility of frames. Finally, the ductility of the most frames of this research could be estimated by using the combination of genetic algorithm and artificial neural networks properly.
Key Words
    moment frame; ductility; nonlinear static analysis; genetic algorithm; artificial neural networks
Moosa Mazloom: Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
Hossein Afkar: Department of Civil Engineering, Technical and Vocational University, Torbat-Heydariyh, Iran
Pardis Pourhaji: Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

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