一种基于元胞自动机的城市多模式扩展模拟方法及系统
By combining the maximum entropy model and the nearest neighbor propagation clustering model with a cellular automata method, the problem of balancing leapfrog and adjacency expansion in urban expansion simulation is solved, realizing the control and accurate simulation of urban growth process, and is applicable to multi-modal expansion of large-scale urban spaces.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUHAN UNIV
- Filing Date
- 2023-04-03
- Publication Date
- 2026-07-17
AI Technical Summary
Existing urban expansion simulation models struggle to simultaneously account for both leapfrog and adjacency expansion patterns, exhibiting significant randomness and difficulty in controlling the process and scale of urban growth.
A cellular automaton approach that couples the maximum entropy model (MaxEnt) and the nearest neighbor propagation clustering model (AP) is adopted to simultaneously simulate skip expansion and adjacency expansion by predicting candidate regions for skip expansion, screening seed points, and introducing growth coefficients.
It reduces the randomness of seed points, enabling more accurate control over the process and scale of urban growth, making it suitable for simulations of a wider range of cities, and improving simulation accuracy and the representation of morphological features.
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Figure CN116542133B_ABST