Yingning Shen

ORCID: 0000-0001-6769-4420
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About
Contact & Profiles
Research Areas
  • Archaeological Research and Protection
  • Color perception and design
  • Environmental Sustainability in Business
  • Remote Sensing and Land Use
  • Land Use and Ecosystem Services
  • Computational and Text Analysis Methods
  • Sustainability and Ecological Systems Analysis
  • Conservation Techniques and Studies
  • Evaluation Methods in Various Fields
  • Environmental Education and Sustainability
  • Cultural Heritage Management and Preservation
  • Sustainable Supply Chain Management
  • Sport and Mega-Event Impacts
  • Quality Function Deployment in Product Design
  • Ergonomics and Musculoskeletal Disorders
  • 3D Surveying and Cultural Heritage
  • Wildlife-Road Interactions and Conservation
  • Impact of Light on Environment and Health
  • Eurasian Exchange Networks
  • Regional Development and Environment

Northwest University
2023-2024

Xiamen University
2022-2024

Building on the observation of gaps in current research, this study provides a comprehensive analysis spatial patterns heritage sites along Silk Road, focusing how historical trade routes shaped what are now recognized as sites. Using data from United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage List, research examines across Eurasia North Africa, with specific emphasis Road corridors. This employs spatiotemporal approach, categorizing into northern...

10.3390/land13091401 article EN cc-by Land 2024-08-30

Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, plays an important role expression of urban territory, humanity style. However, because difficulty measurement, study street has been difficult achieve large-scale fine development. The measurement received attention from many disciplines. With development promotion information technology, maturity view big data deep learning technology provided ideas for research...

10.1371/journal.pone.0289305 article EN cc-by PLoS ONE 2023-11-30

In this study, we apply text analysis and machine learning algorithms to study how improve the satisfaction of Xiamen's green development. Through binary logical regression XGBoost algorithm, find out important factors that affect development establish a equation. public complaint reply data captured in consultation module Xiamen Ecological Environment Bureau, word frequency statistics semantic networks. According research results, proposed strategies Xiamen.

10.1109/scset58950.2023.00049 article EN 2023-04-01

In this study, the AHP-entropy weight method is used to weigh various indicators that affect green development, establish urban development evaluation indicators, and then explore important factors people's satisfaction with through Classification Regression Tree algorithm. Finally, a prediction model established. It was found classification regression results of CART algorithm have high accuracy. The city's coverage area indicator most method. By using algorithm, affecting citizens' Xiamen...

10.1109/scset58950.2023.00115 article EN 2023-04-01

In this study, we used the XGBoost algorithm to discuss importance of green development satisfaction through questionnaire data and found that in terms satisfaction, government’s actions were most important, followed by public transport space other infrastructure provided government, enterprise’s production performance ranked third. From structural equation model, know not only directly affect people’s with but also behavior enterprises. Under causal relationship government supervision...

10.1109/3cbit57391.2022.00056 article EN 2022-10-01
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