Xiangyang Feng
Biographic Data
| ID | 6702634 |
|---|---|
| NAME | Xiangyang Feng |
| GIVEN NAMES | Xiangyang |
| FAMILY NAME | Feng |
| SIGNATURE | FENG X |
| AFFILIATIONS | School of Public Policy and Management China University of Mining and Technology Xuzhou China |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Mapping Soil Organic Carbon in High‐standard Farmland Construction Areas Using Machine Learning Algorithms
Accurate mapping soil organic carbon (SOC) in high‐standard farmland (HSF) construction areas is essential for optimizing agricultural management practices and achieving carbon sequestration. However, how to quantify the construction activities of HSF and predict SOC is still unclear. In this study, we proposed a framework to quantify the impacts of HSF construction activities on SOC from four perspectives: landscape pattern, agricultural infrast…
Information Management and User Engagement in Corporate Social Responsibility Communication
China and America are world’s leading countries in technology, digitalization and advanced systems. Both countries seek to maximize their system qualities and customer-centered services to capture their engagement and long-term interaction. In this domain, this study investigated the impact of information system factors on users’ engagement with the mediation of corporate social responsibility (CSR). This study was structured according to quantit…
No prominent works on this page.
Information Management and User Engagement in Corporate Social Responsibility Communication
China and America are world’s leading countries in technology, digitalization and advanced systems. Both countries seek to maximize their system qualities and customer-centered services to capture their engagement and long-term interaction. In this domain, this study investigated the impact of information system factors on users’ engagement with the mediation of corporate social responsibility (CSR). This study was structured according to quantit…
Mapping Soil Organic Carbon in High‐standard Farmland Construction Areas Using Machine Learning Algorithms
Accurate mapping soil organic carbon (SOC) in high‐standard farmland (HSF) construction areas is essential for optimizing agricultural management practices and achieving carbon sequestration. However, how to quantify the construction activities of HSF and predict SOC is still unclear. In this study, we proposed a framework to quantify the impacts of HSF construction activities on SOC from four perspectives: landscape pattern, agricultural infrast…
Computer Science (2 works) · Agricultural engineering (1 work) · Algorithm (1 work) · Artificial Intelligence (1 work) · Business (1 work) · Communication and COVID-19 Impact (1 work) · Corporate social responsibility (1 work) · Econometrics (1 work) · Engineering (1 work) · Environmental Science (1 work)