| 街道视角的多智能体城市安全宜居度建模 |
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| 引用本文： | 潘理虎,杨芬玉,芦飞平,秦世鹏.街道视角的多智能体城市安全宜居度建模[J].应用科学学报,2022,40(1):47-60. |
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| 作者姓名： | 潘理虎 杨芬玉 芦飞平 秦世鹏 |
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| 作者单位： | 1. 太原科技大学 计算机科学与技术学院, 山西 太原 030024;2. 中国科学院 地理科学与资源研究所, 北京 100101 |
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| 基金项目： | 中国科学院战略性先导科技专项基金（No.XDA20010000）；深圳市战略新兴产业发展专项资金（No.JSGG20170413173425899）；山西省-中科院科技合作重大项目基金（No.20151101001）；山西省研究生教育创新项目基金（No.2020SY439）资助 |
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| 摘 要： | 为解决环境及人类活动因素影响下的城市安全宜居问题,以深圳市福田区10个街道的实际数据为基础,结合Repast仿真平台和地理信息系统(geographic information system,GIS)建立基于多智能体的城市安全宜居度仿真模型;从街道视角模拟福田区未来20 a(年)城市安全发展的演变过程,用情景实例论证分...
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| 关 键 词： | 城市宜居评价 安全宜居度 居民满意度 多智能体建模 街道视角 |
| 收稿时间： | 2020-08-25 |
Modeling of Multi-agent City Safety and Livability Based on Street Perspective |
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| PAN Lihu,YANG Fenyu,LU Feiping,QIN Shipeng.Modeling of Multi-agent City Safety and Livability Based on Street Perspective[J].Journal of Applied Sciences,2022,40(1):47-60. |
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| Authors: | PAN Lihu YANG Fenyu LU Feiping QIN Shipeng |
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| Institution: | 1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, Shanxi, China;2. Institute of Geographical Sciences and Resources, Chinese Academy of Sciences, Beijing 100101, China |
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| Abstract: | In order to solve the problem of urban safety livability under the influence of environmental and human activities, this paper builds a multi-agent model of city safety livability based on the data of ten streets in Futian District, Shenzhen. The model is realized by integrating geographic information system (GIS) with Repast simulation platform. With the model, we have simulated the evolution of urban safety development in Futian District in the next 20 years from the perspective of streets, and analyzed the dynamic interactive feedback mechanism of safety livability, resident satisfaction, and family relocation behavior of each street in Futian District. The simulation experiment proves that the multi-agent model is effective for predicting urban development under the influence of multiple factors. |
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| Keywords: | evaluation of city livability safe livability resident satisfaction multi-agent modeling street perspective |
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