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Water Resources Carrying Capacity and Circular Economy Based on Fuzzy Multilayer Algorithm
1Digital Economy Academy, Yango University, Fuzhou, Fujian 350015, China.
Computational Intelligence and Neuroscience
|August 29, 2022
Summary
This study develops a fuzzy evaluation model to assess water environment carrying capacity and optimize resource management. Findings aid sustainable industrial development through integrated data platforms.
Area of Science:
- Environmental Science
- Water Resource Management
- Ecosystem Analysis
Background:
- Effective water resources environmental management is crucial for sustainable development.
- Assessing the carrying capacity of water environments requires integrated data and robust models.
- Understanding spatial-temporal variations in water resources is key to effective management.
Purpose of the Study:
- To establish an index system for evaluating water environment carrying capacity.
- To analyze the current situation and temporal-spatial characteristics of water resources.
- To support sustainable industrial chain development through data-driven insights.
Main Methods:
- Integration of fuzzy algorithms and water resources environmental management theories.
- Application of a comprehensive multilevel fuzzy evaluation model with scenario analysis.
- Utilizing information entropy and ArcGIS for spatial analysis of water use patterns.
Main Results:
- Evaluation of the water environment's carrying capacity and recent temporal-spatial variations.
- Identification of spatial structures in water use through information entropy and ArcGIS mapping.
- Demonstration of a data platform's utility in optimizing logistics, energy, and waste recycling.
Conclusions:
- The fuzzy evaluation model effectively assesses water environment carrying capacity.
- Spatial analysis tools reveal critical patterns in water resource utilization.
- Data platforms are essential for achieving circular economy principles and sustainable industrial ecosystems.
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