Yuanyuan Wang

ORCID: 0000-0003-1246-4219
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About
Contact & Profiles
Research Areas
  • Air Quality Monitoring and Forecasting
  • Air Quality and Health Impacts
  • Vehicle emissions and performance
  • Energy, Environment, Economic Growth
  • Environmental Impact and Sustainability
  • Complex Network Analysis Techniques
  • COVID-19 impact on air quality
  • Advanced Clustering Algorithms Research
  • Advanced Graph Neural Networks
  • Data Mining Algorithms and Applications
  • Climate Change Policy and Economics

Capital University of Economics and Business
2023

Lanzhou University of Finance and Economics
2020-2023

Shanxi University of Finance and Economics
2022

Lanzhou University
2017

Global trade drives the world’s economic development, while a large amount of embodied carbon is transferred among different countries and regions. Based on multi-regional input–output model, transfers bilateral between 185 countries/regions around world were calculated. On basis, regional transfer patterns major national in six continents, eight cooperation organizations, representative further analyzed. The results showed that Europe was continent with largest inflows from Africa outflows...

10.3390/ijerph192114605 article EN International Journal of Environmental Research and Public Health 2022-11-07

In the context of rapid economic development, air pollution has emerged as a critical environmental issue, particularly in Beijing-Tianjin-Hebei region. This study, through application Air Quality Index (AQI) data and K-means clustering, investigates seasonal variations spatial distribution quality this It been identified that area is not only subject to fluctuation but also exhibits distinct patterns local aggregation. Utilizing Back Propagation (BP) Neural Network model, research predicts...

10.56578/ocs020402 article EN cc-by Opportunities and Challenges in Sustainability 2023-11-28

Community detection is an effective exploration technique for analyzing networks. Most of the network data not only describes connections nodes but also properties nodes. In this paper, we propose a community method collects relevant evidences from information node attributes and structure to assist task on node-attributed We find communities in framework semidefinite programming (SDP) method. practical applications, distribution some may be uncorrelated with or itself contain no as random...

10.1080/03610918.2020.1847291 article EN Communications in Statistics - Simulation and Computation 2020-11-17
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