A cross-regional metabolic prediction method for industrial solid waste based on a combined model
By constructing a physical input-output matrix and a combined prediction model, the key sectors and interactions of industrial solid waste are identified, solving the challenges of full life-cycle analysis and cross-regional collaborative governance of industrial solid waste, and improving the efficiency and safety of industrial solid waste management.
Patent Information
- Application Number
- CN202610436790.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-03
- Publication Date
- 2026-06-30
AI Technical Summary
Existing research has failed to effectively incorporate industrial solid waste into the urban material flow cycle system, making it difficult to achieve full life cycle analysis and optimization. Cross-regional collaborative governance lacks quantitative characterization, hazardous waste disposal risk assessment is weak, and industrial solid waste utilization efficiency is low.
A combined model-based approach is adopted. By constructing a physical input-output matrix, key sectors and their interactions are identified. Combining grey prediction and autoregressive differential moving average models, a combined prediction model is established to simulate the dynamic trends of cross-regional industrial solid waste generation and metabolism, and to output an optimized path.
It enables the analysis and optimization of industrial solid waste from a full life cycle perspective, improves the accuracy and safety of cross-regional collaborative governance, identifies key sectors and their interactions, and provides decision-making basis for management departments.
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Figure CN122311548A_ABST