Min Duan

ORCID: 0009-0007-3414-3690
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About
Contact & Profiles
Research Areas
  • Air Quality and Health Impacts
  • Air Quality Monitoring and Forecasting
  • Regional resilience and development
  • Health disparities and outcomes
  • Entrepreneurship Studies and Influences
  • Firm Innovation and Growth
  • Healthcare Systems and Reforms
  • Vehicle emissions and performance

Nanjing Agricultural University
2022-2024

The escalating issue of air pollution in China’s rapidly developing urban areas has prompted increased attention to the role meteorological conditions PM2.5 pollution. This study examines spatiotemporal distribution concentrations and their relationship with factors six major Chinese agglomerations from 2017 2020, using daily average data. Statistical spatial analysis techniques are employed, alongside construction eight machine learning models for prediction purposes. also compares feature...

10.3390/atmos14050903 article EN cc-by Atmosphere 2023-05-22

Air pollution is a hotspot of wide concern in Chinese cities. With the worsening air pollution, urban agglomerations face an increasingly complex environment for quality monitoring, hindering sustainable and high-quality development China. More effective methods predicting are urgently needed. In this study, we employed seven single models ensemble learning algorithms constructed hybrid algorithm, LSTM-SVR model, totaling eight machine algorithms, to predict Quality Index six major We...

10.3390/atmos14101478 article EN cc-by Atmosphere 2023-09-24

Abstract The contradiction between supply and demand of China's health resources has become increasingly prominent under the strategic requirement “High-quality public development”. Especially in context accelerated population aging changes disease spectrum, chronic diseases other issues are concerned. government, as main supplier, have to solve outstanding conflicts imbalance resource allocation region. Our study aims analyze inequalities utilization behavior basic services for diseases,...

10.21203/rs.3.rs-1611220/v1 preprint EN cc-by Research Square (Research Square) 2022-05-31
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