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- Title
基于智能体和人工神经网络的元胞自动机建模及城市扩展模拟.
- Authors
陶奕宏; 王海军; 张 彬; 曾浩然; 孙 晶
- Abstract
The human decision-making behavior plays an important role in urban expansion process・ However, it is often ignored in the cellular automata(CA) modeling of urban expansion. To overcome this limitation, this study adopts the agent-based model (ABM) to characterize the effects ol human decision-making behaviors and couples it with the artificial neural network (ANN) to derive the transition rules of CA models. The ANN-ABM-CA model has the ability to couple the sell-organization and human decision-making behaviors in the simulation of urban expansion process, and can provide supports for the sustainable development ol the city. Meanwhile, the decision-making behaviors of macro agen t (government) and micro agent (residents from three income levels) have been built, which can explain the driving mechanism ol urban expansion in a better way. Then the urban expansion of main urban area of Wuhan from 2005 to 2015 was simulated with 10 driving factors. The results show that:l) The overall accuracy(OA) value is 97. 46%, Kappa coefficient is 0. 9176 and the figure of merit (FoM) value is 0. 4375, the accuracy of simulation has been significantly improved comparing with the traditional ANN-CA model 2) Residents of different income levels have different development preferences for urban expansion・ 3) The urban expansion pattern of Wuhan's main urban area in simulation results is mainly marginal expansion, with a small part of filling expansion in the southwest of Hongshan District and enclave expansion in the southeast of Hongshan District, which is consistent with the actual expansion situation.
- Subjects
WUHAN (China); CITIES &; towns; URBAN growth; CELLULAR automata; SUSTAINABLE urban development; SUSTAINABLE development; ARTIFICIAL neural networks
- Publication
Geography & Geographic Information Science, 2022, Vol 38, Issue 1, p79
- ISSN
1672-0504
- Publication type
Article
- DOI
10.3969/j.issn.1672--0504.2022.01.012