Principal Component Analysis-Based Data Clustering for Labeling of Level Damage Sector in Post-Natural Disasters-Reference-Cited by-同舟云学术

Principal Component Analysis-Based Data Clustering for Labeling of Level Damage Sector in Post-Natural Disasters

Published:2023 Issue: Volume:11 Page:74590-74601
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Almais Agung Teguh Wibowo¹^ORCID,Susilo Adi¹^ORCID,Naba Agus¹^ORCID,Sarosa Moechammad²,Crysdian Cahyo³,Tazi Imam³,Hariyadi Mokhamad Amin³,Muslim Muhammad Aziz⁴,Basid Puspa Miladin Nuraida Safitri Abdul³,Arif Yunifa Miftachul³^ORCID,Purwanto Mohammad Singgih⁵,Parwatiningtyas Diyan⁶,Supriyono ³,Wicaksono Hendro⁷^ORCID

Affiliation:

1. Department of Physics, Universitas Brawijaya Malang, Malang, Indonesia

2. Department of Electrical Engineering, State Polytechnic of Malang, Malang, Indonesia

3. Department of Informatics Engineering, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Malang, Indonesia

4. Department of Electrical Engineering, Universitas Brawijaya, Malang, Indonesia

5. Department of Geophysical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

6. Department of Physics, Universitas Pertahanan Republik Indonesia, Bogor, Indonesia

7. School of Business, Social and Decision Science, Constructor University, Bremen, Germany

Funder

International Collaborative Development Research in 2022

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10123944.pdf?arnumber=10123944

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4. Preliminary design of spatio-temporal disaster database in Indonesia to support emergency response