Artificial-Intelligence-Based Methods for Structural Health Monitoring-Reference-Cited by-同舟云学术

Artificial-Intelligence-Based Methods for Structural Health Monitoring

Published:2022-12-12 Issue:24 Volume:12 Page:12726
ISSN:2076-3417
Container-title:Applied Sciences
language:en
Short-container-title:Applied Sciences

Author:

Altabey Wael A.^ORCID,Noori Mohammad^ORCID

Abstract

Intelligent and resilient infrastructure and smart cities make up a rapidly emerging field that is redefining the future of urban development and ways of preserving the existing infrastructure against natural hazards...

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Link

https://www.mdpi.com/2076-3417/12/24/12726/pdf

Reference16 articles.

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3. Ghiasi, R., Noori, M., Kuok, S.-C., Silik, A., Wang, T., Pozo, F., and Altabey, W.A. (2022). Structural Assessment under Uncertain Parameters via the Interval Optimization Method Using the Slime Mold Algorithm. Appl. Sci., 12.

4. Ghiasi, R., Noori, M., Altabey, W.A., Silik, A., Wang, T., and Wu, Z. (2021). Uncertainty Handling in Structural Damage Detection via Non-Probabilistic Meta-Models and Interval Mathematics, a Data-Analytics Approach. Appl. Sci., 11.

5. Shi, J., Dang, J., Cui, M., Zuo, R., Shimizu, K., Tsunoda, A., and Suzuki, Y. (2021). Improvement of Damage Segmentation Based on Pixel-Level Data Balance Using VGG-Unet. Appl. Sci., 11.

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