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An innovative approach for modeling of hysteretic energy demand in steel moment resisting frames

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Abstract

This paper presents a new nonlinear model for the prediction of hysteretic energy demand in steel moment resisting frames using an innovative genetic-based simulated annealing method called GSA. The hysteretic energy demand was formulated in terms of several effective parameters such as earthquake intensity, number of stories, soil type, period, strength index, and energy imparted to the structure. The performance and validity of the model were further tested using several criteria. The proposed model provides very high correlation coefficient (R = 0.985), and low root mean absolute error (RMSE = 1,346.1) and mean squared error (MAE = 1,037.6) values. The obtained results indicate that GSA is an effective method for the estimation of the hysteretic energy. The proposed GSA-based model is valuable for routine design practice. The prediction performance of the optimal GSA model was found to be better than that of the existing models.

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Authors and Affiliations

  1. Department of Civil Engineering, The University of Akron, Akron, OH, 44325, USA

    Amir Hossein Gandomi

  2. Department of Civil and Environmental Engineering, Engineering Building, Michigan State University, East Lansing, MI, 48824, USA

    Amir Hossein Alavi

  3. Department of Civil Engineering, Urmia University of Technology, P.O. Box: 57155-419, Urmia, Iran

    Abazar Asghari

  4. Department of Civil Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran

    Hadi Niroomand & Ali Matin Nazar

Authors
  1. Amir Hossein Gandomi
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  2. Amir Hossein Alavi
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  3. Abazar Asghari
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  4. Hadi Niroomand
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  5. Ali Matin Nazar
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Correspondence to Amir Hossein Alavi.

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Gandomi, A.H., Alavi, A.H., Asghari, A. et al. An innovative approach for modeling of hysteretic energy demand in steel moment resisting frames. Neural Comput & Applic 24, 1285–1291 (2014). https://doi.org/10.1007/s00521-013-1342-x

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