Rongyun Tang Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Postdoc
postdoc
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Biography and Research Information
OverviewAI-generated summary
Rongyun Tang's research investigates decision-making models in manufacturing and e-commerce supply chains, particularly concerning carbon emission permits and capital constraints. Tang has also explored the interannual variability and climatic sensitivity of global wildfire activity, developing models that incorporate ensemble machine learning and satellite observations for fire prediction and control. Further work examines the impact of heatwave events on hydrological processes in the contiguous United States and quantifies wildfire drivers in boreal peatlands using machine learning frameworks. Tang's publications also address low-carbon e-commerce supply chains and sustainable development, as well as coordination strategies in e-commerce logistics under specific preferences. Tang has published 18 papers with 391 citations and an h-index of 10.
Metrics
- h-index: 10
- Publications: 18
- Citations: 402
Selected Publications
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Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0 (2024)
Collaboration Network
Top Collaborators
- Interannual variability and climatic sensitivity of global wildfire activity
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)
- Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
- TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework
Showing 5 of 7 shared publications
- Interannual variability and climatic sensitivity of global wildfire activity
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)
- Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
- TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework
Showing 5 of 7 shared publications
- Interannual variability and climatic sensitivity of global wildfire activity
- Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
- TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework
- Supplementary material to "TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework"
- Comment on gmd-2023-14
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
- TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework
- Supplementary material to "TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework"
- Comment on gmd-2023-14
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
- TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework
- Supplementary material to "TSECfire v1.0: Quantifying Wildfire Drivers and Predictability in Boreal Peatlands Using a Two-Step Error-Correcting Machine Learning Framework"
- Comment on gmd-2023-14
- Manufacturer’s decision-making model under carbon emission permits repurchase strategy and capital constraints
- Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development
- Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences
- Advertising and pricing of online direct selling considering network externalities
- Manufacturer’s decision-making model under carbon emission permits repurchase strategy and capital constraints
- Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development
- Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences
- Advertising and pricing of online direct selling considering network externalities
- Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences
- Advertising and pricing of online direct selling considering network externalities
- Manufacturer’s decision-making model under carbon emission permits repurchase strategy and capital constraints
- Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development
- Interannual variability and climatic sensitivity of global wildfire activity
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Interannual variability and climatic sensitivity of global wildfire activity
- Global fire modelling and control attributions based on the ensemble machine learning and satellite observations
- Interannual variability and climatic sensitivity of global wildfire activity
- Evaluating the effects of heatwave events on hydrological processes in the contiguous United States (2003–2022)
- Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences
- Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development
- Carbon Trading Mechanism, Low-Carbon E-Commerce Supply Chain and Sustainable Development
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