This study delves into the transformative influence of Machine Learning (ML), Deep
Learning (DL), and Artificial Intelligence (AI) within the realm of Structural Engineering …

In this study, four machine learning (ML) algorithms, namely Support Vector Machine (SVM),
Back-propagation Artificial Neural Network (BP-ANN), Adaptive Boosting (AdaBoost), and …

Crack is the earliest indication of structural deterioration. It is necessary to examine the
structural elements as cracks can affect the durability and safety of civil infrastructures …

This research paper delves into the integration of advanced generative artificial intelligence
(AI) models, such as ChatGPT, Bard, and similar architectures, within the realms of …

Occupational health risks such as falls from height, electrocution, object strikes, mechanical
injuries, and collapses have plagued the construction industry. Deep learning algorithms are …

Accurately forecasting construction delay risks is essential for effective project management
in the construction industry. This study evaluates the performance of three machine learning …

Geotechnical site characterization is a crucial factor in the effective planning, design, and
implementation of civil engineering projects. In the evolving landscape of infrastructure …

Conventionally, civil engineering is the branch mainly related to the construction of
buildings, bridges, highways, etc. Presently, the scope of civil engineering is widening, and …

Purpose Prediction models are essential tools for transportation agencies to forecast the
condition of bridge decks based on available data, and artificial intelligence is paramount for …

The integration of Artificial Intelligence (AI) techniques in the optimization of steel moment
frame structures represents a transformative approach to enhance the design, analysis, and …