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Ecosphere Management Model of Farmer Cooperatives Based on Intelligent Data Sampling Technology
Ting Fang1, Xiaoming Liao1, Ming Fang2
1School of Public Administration, Nanchang University, Nanchang 330031, China.
Computational Intelligence and Neuroscience
|April 4, 2022
Summary
This study enhances farmer cooperative operations using intelligent data sampling. The proposed ecosystem business model improves efficiency and regional development through data analysis and system building.
Area of Science:
- Agricultural Economics
- Data Science
- Systems Engineering
Background:
- Farmer cooperatives face operational challenges impacting efficiency.
- The integration of intelligent data sampling offers potential for optimization.
- Existing ecosphere models require enhancement for sustainable regional development.
Purpose of the Study:
- To improve the operational effectiveness of farmer cooperatives.
- To analyze and promote an ecosphere business model for regional development.
- To develop and implement a data-driven system for cooperative management.
Main Methods:
- Intelligent data sampling technology for analyzing cooperative ecosphere operations.
- In-depth study of TI-ADC modeling, error estimation, and mismatch compensation.
- System architecture design based on cooperative ecosphere management needs.
- Analysis of data processing layer structure and flow.
Main Results:
- The proposed ecosystem business model demonstrated positive operational outcomes.
- Intelligent data analysis provided insights into cooperative ecosphere dynamics.
- A functional system structure was developed for cooperative management.
- Engineering realization of advanced data processing technologies was achieved.
Conclusions:
- The intelligent data sampling-based ecosystem business model is effective for farmer cooperatives.
- The study provides a framework for data-driven management and regional development.
- Further research can explore advanced TI-ADC modeling and compensation techniques.
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