Prediction of seismic damage spectra using computational intelligence methods
المؤلف | Gharehbaghi, Sadjad |
المؤلف | Gandomi, Mostafa |
المؤلف | Plevris, Vagelis |
المؤلف | Gandomi, Amir H. |
تاريخ الإتاحة | 2023-12-06T09:34:56Z |
تاريخ النشر | 2021 |
اسم المنشور | Computers and Structures |
المصدر | Scopus |
الرقم المعياري الدولي للكتاب | 457949 |
الملخص | Predicting seismic damage spectra, capturing both structural and earthquake features, is useful in performance-based seismic design and quantifying the potential seismic damage of structures. The objective of this paper is to accurately predict the seismic damage spectra using computational intelligence methods. For this purpose, an inelastic single-degree-of-freedom system subjected to a set of earthquake ground motion records is used to compute the (exact) spectral damage. The Park-Ang damage index is used to quantify the seismic damage. Both structural and earthquake features are involved in the prediction models where multi-gene genetic programming (MGGP) and artificial neural networks (ANNs) are applied. Common performance metrics were used to assess the models developed for seismic damage spectra, and indicated that their accuracy was higher than a corresponding model in the literature. Although the performance metrics revealed that the ANN model is more accurate than the MGGP model, the explicit MGGP-based mathematical model renders it more practical in quantifying the potential seismic damage of structures. |
اللغة | en |
الناشر | Elsevier |
الموضوع | Artificial neural networks Computational intelligence Genetic programming Inelastic SDOF systems Park-Ang damage index Regression analysis Resiliency Seismic damage spectra |
النوع | Article |
رقم المجلد | 253 |
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