Άρθρα σε Περιοδικά

Άρθρα σε διεθνή επιστημονικά περιοδικά με κριτές

X. Lu*, V. Plevris, G. Tsiatas, D. De Domenico, “Editorial: Artificial Intelligence-powered Methodologies and Applications in Earthquake and Structural Engineering”, Frontiers in Built Environment, 8:876077, 2022. DOI: 10.3389/fbuil.2022.876077


Abstract:
Earthquake disasters have caused enormous casualties and economic losses so far, threatening the social and economic development of humanity. At present, artificial intelligence (AI) is one of the frontiers and central issues in both academic research and engineering practice. AI refers to the branch of computer science that develops machines and software with human-like intelligence. In recent years, AI techniques are developing rapidly and have been widely adopted in several engineering disciplines. Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have recently acquired considerable attention and are establishing themselves as a new class of powerful intelligent methods for use in the earthquake and structural engineering with proven effectiveness, as shown in recent studies. In the future, with the improvement of computational power and data accumulation, the feasibility and necessity of AI-driven technologies are expected to grow quickly. The Research Topic “Artificial Intelligence-Powered Methodologies and Applications in Earthquake and Structural Engineering” was proposed to collect cutting-edge research works combining AI with various scientific fields, such as seismic ground motion studies, structural and city-scale seismic risk, computational methods in structural engineering, structural system identification and damage detection, structural control under seismic action, structural health monitoring, among others.



Keywords:
artificial intelligence, seismic risk, damage assessment, system identification, structural dynamics and control, structural health monitoring, damage detection.