Understanding the user-generated geographic information by utilizing big data analytics for health care
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Dosyalar
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
HINDAWI LTD
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
There are two main ways to achieve an active lifestyle, the first is to make an effort to exercise and second is to have the activity as part of your daily routine. The study's major purpose is to examine the influence of various kinds of physical engagements on density dispersion of participants in Shanghai, China, and even prototype check-in data from a Location-Based Social Network (LBSN) utilizing a mix of spatial, temporal, and visualization methodologies. This paper evaluates Weibo used for big data evaluation and its dependability in some types rather than physically collected proofs by investigating the relationship between time, class, place, frequency, and place of check-in built on geographic features and related consequences. Kernel density estimation has been used for geographical assessment. Physical activities and frequency allocation are formed as a result of hour-to-day consumption habits. Our observations are based on customer check-in activities in physical venues such as gyms, parks, and playing fields, the prevalence of check-ins, peak times for visiting fun parks, and gender disparities, and we applied relative difference formulation to reveal the gender difference in a much better way. The purpose of this research is to investigate the influence of physical activity and health-related standard of living on well-being in a selection of Shanghai inhabitants. Keywords
Açıklama
Anahtar Kelimeler
Kaynak
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
WoS Q Değeri
Q2
Scopus Q Değeri
N/A
Cilt
2022
Sayı
Künye
Ullah, H., Hameed, A. A., Rizvi, S. S., Jamil, A., & Kwon, S. J. (2022). Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care. Computational Intelligence and Neuroscience, 2022.
