Clustering and Selection of Hurricane Wind Records Using Autoencoder and k-Means Algorithm-Reference-Cited by-同舟云学术

Clustering and Selection of Hurricane Wind Records Using Autoencoder and k-Means Algorithm

Author:

Du Xinlong¹^ORCID,Hajjar Jerome F.²,Bond Robert Bailey³,Ren Pu⁴^ORCID,Sun Hao⁵

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Northeastern Univ., Boston, MA 02115 (corresponding author). ORCID: .

2. CDM Smith Professor and Chair, Dept. of Civil and Environmental Engineering, Northeastern Univ., Boston, MA 02115.

3. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Northeastern Univ., Boston, MA 02115.

4. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Northeastern Univ., Boston, MA 02115. ORCID: .

5. Associate Professor, Gaoling School of Artificial Intelligence, Renmin Univ. of China, Beijing 100872, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science,Building and Construction,Civil and Structural Engineering

Link

Reference57 articles.

3. ASCE. 2016a. “ASCE 7 hazard tool.” Accessed October 17 2021. https://asce7hazardtool.online/.

4. ASCE. 2016b. Minimum design loads and associated criteria for buildings and other structures (ASCE Standard 7-16). Reston, VA: ASCE.

5. ASCE. 2019. Prestandard for performance–based wind design. Reston, VA: ASCE.

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