I am very much interested to start learning and applying ML techniques to wind engineering problems. I was wondering if I can find some research papers on the application of basic Machine learning techniques to structural wind engineering (including bluff body aerodynamics and aerodynamic behavior of structures under different wind events.) Where should I start if I have a basic knowledge of ML?
(Note: I know the websites, but I wanted to get an idea of the papers which used basic ML in wind engineering).
You can find research papers on simple machine learning techniques applied to structural wind engineering in various academic databases and search engines. Here are some suggestions:Google Scholar: This is a free search engine that indexes scholarly literature, including research papers, theses, books, and conference proceedings. You can search for keywords such as "machine learning," "structural wind engineering," and "simple techniques" to find relevant papers.IEEE Xplore: This is a digital library of scientific and technical content published by the Institute of Electrical and Electronics Engineers (IEEE). It includes conference proceedings, journals, and standards related to engineering, computer science, and technology. You can search for papers using keywords or browse the topics related to wind engineering and machine learning.ScienceDirect: This is a subscription-based database of scientific literature, including journals, books, and conference proceedings. It covers various disciplines, including engineering, computer science, and mathematics. You can search for papers related to structural wind engineering and machine learning using keywords and filters.ASCE Library: This is a digital library of publications by the American Society of Civil Engineers (ASCE), including journals, conference proceedings, and standards related to civil engineering. You can search for papers related to wind engineering and machine learning by using keywords and filters.arXiv: This is an open-access repository of scholarly articles in various fields, including physics, mathematics, computer science, and engineering. It allows researchers to upload preprints of their papers, which are often unpublished or undergoing peer-review. You can search for papers related to wind engineering and machine learning using keywords and filters.When searching for papers, it's important to use relevant keywords and to filter the results by publication date, author, and other criteria to ensure that you find the most recent and relevant papers. Additionally, you may want to consult with your university library or a research librarian for more specific recommendations and search strategies.
1: To find articles, use Google Scholar or trustable journals in this field. Please see this link:
https://scholar.google.com/scholar?hl=en&assdt=0%2C5&q=wind+engineering+%2B+deep+learning&btnG=&oq=wind+engineering+%2B+deep+le
2: You will surely need to understand the concepts of machine learning, and training courses can help you with this. Alternatively, read books in this field. "François Chollet's Deep Learning with Python-Manning" is one of the best books.
There are several ways to find research papers on the application of basic machine learning techniques to structural wind engineering. Here are a few suggestions:
Here are a few research papers that may be of interest to you:
- "Aerodynamic optimization of high-rise buildings using machine learning techniques" by A. Al-Sammaraie and A. Hamza
- "Application of artificial neural network for wind-induced vibration prediction of a tall building" by L. Wu, et al.
- "A hybrid approach combining computational fluid dynamics and machine learning for aerodynamic force prediction of a high-rise building" by S. Xiao, et al.
- "Wind load forecasting based on machine learning for structural health monitoring of bridges" by L. Feng, et al.
These papers may use more advanced machine learning techniques, but they may still be helpful in understanding how machine learning can be applied to wind engineering problems.
- Badges
- Science topic
- Similar topics
- Engineering
- Modeling