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Journal of the Korea Concrete Institute

J Korea Inst. Struct. Maint. Insp.
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  • Korea Citation Index (KCI)

References

1 
Jeong, S. H., and Jang, W. S. (2017), Development of earthquake safety assessment software for cable-stayed bridges using seismic acceleration measurement data, Journal of the Korea Institute for Structural Maintenance and Inspection, KISMI, 21(1), 337-340. (in Korean)URL
2 
Ahn, J. H., Jeong, J. W., Hong, Y. C., Park, J. B., and Choi, H. S. (2019), Proposal and Evaluation of Ground Response Spectrum Estimation Algorithm based on Seismic Observation Data, Journal of The Korea Institute for Structural Maintenance and Inspection, 23(5), 13-22. (in Korean)URL
3 
Lee, K. S., Ahn, J. H., Park, H. Y., Seo, Y. D., and Kim, S. C. (2023), Seismic Acceleration Estimation Method at Arbitrary Position Using Observations and Machine Learning, KSCE Journal of Civil Engineering, 27(2), 712-726. (in Korean)DOI
4 
Abrahamson, N. A., and Somerville, P. G. (1996), Effects of the hanging wall and footwall on ground motions recorded during the Northridge earthquake, Bulletin of the Seismological Society of America, 86(1B), S93-S99. DOI: 10.1785/BSSA08601B0S93DOI
5 
Shiuly, A., Roy, N., and Sahu, R. B. (2020), Prediction of peak ground acceleration for Himalayan region using artificial neural network and genetic algorithm, Arabian Journal of Geosciences, 13(215). DOI: 10.1007/s12517-020-5211-5DOI
6 
Khosravikia, F., and Clayton, P. (2021) Machine learning in ground motion prediction, Computers and Geosciences, 148, 104700. DOI: 10.1016/j.cageo.2021.104700DOI
7 
Irvine, T. (2002), An introduction to the shock response spectrum, Vibrationdata.URL
8 
Simard, P. Y., SteinKraus, D., and Platt, J. C. (2003), Best practices for convolutional neural networks applied to visual document analysis, Seventh International Conference on Document Analysis and Recognition, Edinburgh, UK, 958-963. DOI: 10.1109/ICDAR.2003.1227801.DOI
9 
Wei, X., Xie, C. W., Wu, J., and Shen, C. (2018), Mask-CNN: Localizing parts and selecting descriptors for fine-grained bird species categorization, Pattern Recognit, 76, 704-714. DOI: 10.1016/j.patcog.2017.10.002.DOI
10 
Kolasa, M., Jóźwicki, W., Wojtyna, R., and Jarzemski, P. (2007), Optimization of hidden layer in a neural network used to predict bladder-cancer patient-survival, SPA Conference, Poland. DOI: 10.1109/SPA.2007.5903302DOI
11 
Liu, Y., Starzyk, J. A., and Zhu, Z. (2007), Optimizing number of hidden neurons in neural networks, IASTED International Conference on Artificial Intelligence and Applications, Austria 1(1), 6.URL
12 
Wagarachchi, N. M., and Karunananda, A. S. (2013), Optimization of multi-layer artificial neural networks using delta values of hidden layers, IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), Singapore. DOI: 10.1109/CCMB.2013.6609169DOI
13 
Zurada, J. M. (1992), Introduction to artificial neural networks systems, West Publishing Company.URL