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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
引用本文:陶奕宏,王海军,张彬,曾浩然,孙晶.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[J].地理与地理信息科学,2022,38(1):79-85.
作者姓名:陶奕宏  王海军  张彬  曾浩然  孙晶
作者单位:武汉大学资源与环境科学学院,湖北 武汉430079
基金项目:国家自然科学基金项目“顾及时空非平稳特征的城市群土地利用演变元胞自动机模型构建”(42171411)。
摘    要:城市扩展模拟可为城市可持续发展与国土空间规划提供参考。智能体模型(ABM)与元胞自动机(CA)结合可兼顾城市空间增长的自组织性和不同决策主体的决策过程,人工神经网络(ANN)可描述智能体与城市扩展之间复杂的非线性关系。该文基于ANN-ABM-CA耦合模型,在构建CA转换规则时基于ABM刻画人类决策行为的影响,并采用ANN挖掘不同类型的智能体在城市扩展过程中的偏好差异,同时考虑宏观和微观层面的智能体决策行为,结合城市扩展的10个驱动因素,模拟武汉市主城区2005-2015年的扩展情况,结果表明:1)相比传统的ANN-CA模型,ANN-ABM-CA模型模拟性能更优,从宏观与微观相结合的角度更好地解释了城市扩展的驱动机制,OA值为97.46%,Kappa系数为0.9176,FoM值为0.4375,结果可靠且合理;2)不同收入层级的居民智能体对城市扩展的决策偏好不同;3)武汉主城区城市扩展模式主要为边缘型扩展,洪山区西南部有少部分填充型扩展、东南部出现飞地型扩展,与实际扩展情况相符。

关 键 词:智能体模型  人工神经网络  城市扩展  元胞自动机  武汉主城区

Modeling of Cellular Automata and Its Simulation of Urban Expansion Based on Agent-Based Model and Artificial Neural Network
TAO Yi-hong,WANG Hai-jun,ZHANG Bin,ZENG Hao-ran,SUN Jing.Modeling of Cellular Automata and Its Simulation of Urban Expansion Based on Agent-Based Model and Artificial Neural Network[J].Geography and Geo-Information Science,2022,38(1):79-85.
Authors:TAO Yi-hong  WANG Hai-jun  ZHANG Bin  ZENG Hao-ran  SUN Jing
Institution:(School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China)
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 of 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 self-organization and human decision-making behaviors in the simulation of urban expansion process,and can provide supports for the sustainable development of the city.Meanwhile,the decision-making behaviors of macro agent(government)and micro agent(residents from three income levels)have been built,which can explain the driving mechanism of 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:1)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.
Keywords:agent-based model  artificial neural network  urban expansion  cellular automata  main urban area of Wuhan
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