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1.
Despite its popularity, agent-based modeling is limited by serious barriers that constrain its usefulness as an exploratory tool. In particular, there is a paucity of systematic approaches for extracting coarse-grained, system-level information as it emerges in direct simulation. This is particularly problematic for agent-based models (ABMs) of complex urban systems in which macroscopic phenomena, such as sprawl, may manifest themselves coarsely from bottom-up dynamics among diverse agent-actors interacting across scales. Often these connections are not known, but treating them is nevertheless crucial in enabling prediction, in supporting decisions, and in facilitating the design, control, and optimization of urban systems. In this article, we describe and implement a metasimulation scheme for extracting macroscopic information from local dynamics of agent-based simulation, which allows acceleration of coarse-scale computing and which may also serve as a precursor to handle emergence in complex urban simulation. We compare direct ABM simulation, population-level equation solutions, and coarse projective integration. We apply the scheme to the simulation of urban sprawl from local drivers of urbanization, urban growth, and population dynamics. Numerical examples of the three approaches are provided to compare their accuracy and efficiency. We find that our metasimulation scheme can significantly accelerate complex urban simulations while maintaining faithful representation of the original model.  相似文献   

2.
Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems. As a process-oriented modelling approach, agent based model(ABM) plays an important role in revealing the driving forces of land change and understanding the process of land change. This paper starts from three aspects: The theory, application and modeling framework of ABM. First, we summarize the theoretical basis of ABM and introduce some related concepts. Then we expound the application and development of ABM in both urban land systems and agricultural land systems, and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region, China. On the basis of combing the ABM modeling protocol, we propose the land system ABM modeling framework and process from the perspective of agents. In terms of urban land use, ABM research initially focused on the study of urban expansion based on landscape, then expanded to issues like urban residential separation, planning and zoning, ecological functions, etc. In terms of agricultural land use, ABM application presents more diverse and individualized features. Research topics include farmers' behavior, farmers' decision-making, planting systems, agricultural policy, etc. Compared to traditional models, ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data. However, due to its unique bottom-up model structure, ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.  相似文献   

3.
土地系统多主体模型的理论与应用   总被引：1，自引：0，他引：1  
戴尔阜  马良  杨微石  王亚慧  尹乐  童苗 《地理学报》2019,74(11):2260-2272
土地变化科学是理解人类—自然耦合系统的交叉学科研究方向。多主体模型（ABM）作为过程导向模型,对揭示土地变化驱动力,理解土地变化过程有重要作用。本文从理论、应用与建模框架三方面出发,总结了ABM理论基础和相关概念;阐述了ABM在城市和农业土地系统两方面的应用与发展,进一步介绍了横断山区退耕还林ABM研究案例;在梳理ABM建模协议的基础上,提出了主体视角的土地系统ABM建模框架和实施流程。在城市土地利用方面,ABM研究从最初基于景观研究城市扩张,到研究城市内部居住分隔,规划分区,生态功能等多方面;在农业土地利用方面,ABM应用则呈现出更加多样化和个性化的特征,包括农民行为、农户决策、种植系统、农业政策等。相比于传统模型,ABM因其依靠本地知识与数据而使得其构建更为复杂,且不易推广;但因其独特的自下而上模型构架,在探究土地变化驱动力、刻画人类行为对自然环境影响等方面具有不可或缺的作用。  相似文献   

4.
In recent years, agent-based models (ABMs) have become a prevalent approach for modelling complex urban systems. As a class of bottom-up method, ABMs are capable of simulating the decision-making as well as the multiple interactions of autonomous agents and between agents and the environment. The definition of agents' behaviour is a vital issue in implementing ABMs to simulate urban dynamics. Urban economic theory has provided effective ways to cope with this problem. This theory argues that the formation of urban spatial structure is an endogenous process resulting from the interactions among individual actors that are spatially distributed. However, this theory is used to explain urban phenomena regardless of spatial heterogeneity in most cases. This study combines GIS, ABM and urban economic models to simulate complex urban residential dynamics. The time-extended model is incorporated into an ABM so as to define agents' behaviour on a solid theoretical basis. A spatial variable is defined to address the neighbourhood effect by considering spatial heterogeneity. The proposed model is first verified by the simulation of three scenarios using hypothetical data: (1) single dominated preference; (2) varying preferences on the basis of income level; and (3) spatially heterogeneous environment. Then the model is implemented by simulating the residential dynamics in Guangzhou, China.  相似文献   

5.
Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for integrating such a sampling design of fieldwork with operational considerations and evaluation of alternative scenarios. However, this fieldwork design driven by SDSS is often computationally intensive and repetitive. In this study, we develop a cyber-enabled SDSS framework to facilitate the computationally challenging fieldwork design that requires the efficacious selection of base camps and plots for the inventory of mangroves. Our study area is the Zambezi River Delta, Mozambique. Cyber-enabled capabilities, including scientific workflows and cloud computing, are integrated with the SDSS. Scientific workflows enable the automation of data and modeling tasks in the SDSS. Cloud computing offers on-demand computational support for interoperation among stakeholders for collaborative scenario evaluation for the fieldwork design of mangrove inventory. Further, this framework allows for harnessing high-performance computing capabilities for accelerating the fieldwork design. The cyber-enabled framework provides significant merits in terms of effective coordination among science and logistical teams, assurance of meeting inventory objectives, and an objective basis to collectively and efficaciously evaluate alternative scenarios.  相似文献   

6.
The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models.  相似文献   

7.
An agent-integrated irregular automata model of urban land-use dynamics   总被引：2，自引：0，他引：2  
Urban growth models are useful tools to understand the patterns and processes of urbanization. In recent years, the bottom-up approach of geo-computation, such as cellular automata and agent-based modeling, is commonly used to simulate urban land-use dynamics. This study has developed an integrated model of urban growth called agent-integrated irregular automata (AIIA) by using vector geographic information system environment (i.e. both the data model and operations). The model was tested for the city of San Marcos, Texas to simulate two scenarios of urban growth. Specifically, the study aimed to answer whether incorporating commercial, industrial and institutional agents in the model and using social theories (e.g. utility functions) improves the conventional urban growth modeling. By validating against empirical land-use data, the results suggest that a holistic framework such as AIIA performs better than the existing irregular-automata-based urban growth modeling.  相似文献   

8.
ABSTRACT

Abstract: When modelling urban expansion dynamics, cellular automata models focus mostly on the physical environments and cell neighbours, but ignore the ‘human’ aspect of the allocation of urban expansion cells. This limitation is overcome here using an intelligent self-adapting multiscale agent-based model. To simulate the urban expansion of Auckland, New Zealand, a total of 15 urban expansion drivers/constraints were considered over two periods (2000–2005, 2005–2010). The modelling takes into consideration both a macro-scale agent (government) and micro-scale agents (residents of three income levels), and their multi-level interactions. In order to achieve reliable simulation results, ABM was coupled with an artificial neural network to reveal the learning process and heterogeneity of the multi-sub-residential agents. The ANN-ABM accurately simulated the urban expansion of Auckland at both the global and local scales, with kappa simulation value at 0.48 and 0.55, respectively. The validated simulation result shows that the intelligent and self-adapting ANN-ABM approach is more accurate than an ABM with a general type of agent model (kappa simulation = 0.42) at the global scale, and more accurate than an ANN-based CA model (kappa simulation = 0.47) at the local scale. Simulation inaccuracy stems mostly from the outdated master land use plan.  相似文献   

9.
基于agent的商业中心地空间结构动态模拟   总被引：1，自引：0，他引：1  
薛领  罗柏宇  翁瑾 《地理研究》2010,29(9):1659-1669
以克里斯泰勒提出的中心地空间结构为研究对象,回顾和总结了中心地理论的主要内容、理论发展和实际应用,并以复杂性科学的理论和方法为基础,根据中心地理论假设,提出基于agent建模的两层次agent模型结构,通过遗传算法再现和验证了克氏单一职能的六边形中心地空间格局。模拟表明,微观自主体的相互作用的确可以突现出六边形宏观空间格局,这为以后突破克氏理论中"均质、静态、封闭"的不足提供了新的研究途径。中心地宏观空间结构的微观机理需要进一步结合经济学演绎模型和ABM的计算实验深入研究。  相似文献   

10.
ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.  相似文献   

11.
运用模拟平台模拟农户土地利用行为,对揭示农户土地利用变化机制和调整土地利用决策具有重要意义。本文选择生态脆弱区一乡一业、一村一品典型村陕西省米脂县姜兴庄为例,以信念—愿望—意图模型(BDI)为基础,构建有限理性能力与资源(CR-BDI)模型。基于NetLogo平台对CR-BDI模型和传统BDI模型的模拟情况进行对比分析,结果表明：①CR-BDI模型更适于微观尺度农户土地利用决策研究。2014年该模型面积失误率为6.78%,比传统BDI模型低8.48%,空间准确率比传统BDI模型高10.10%,2015年CR-BDI模型和传统BDI模型的整体空间正确率分别为78.8%和69.2%;②CR指数有利于体现农户的有限理性,与实际种植决策较为符合;③利用NetLogo平台有利于直观再现农户土地利用行为,揭示土地利用变化的微观机理,可作为研究土地利用变化互动机理的良好平台。  相似文献   

12.
颜秉秋  高晓路  季珏 《地理科学进展》2015,34(12):1586-1597
养老设施规划配置的关键应着眼于老年群体对养老服务的差异化需求及其动态变化特征。本文提出了基于多主体模拟的理论框架,并通过对前期研究的梳理,归纳出养老机构配置问题中需要考虑的老年人、养老机构等主体的时间变异和空间差异特征、其行为规则以及他们与环境之间的相互作用规律。在此基础上,以北京市为例构建了多主体微观模拟模型,对2010-2030年间养老机构需求与供给态势进行了预测,并讨论了养老设施布局的评估指标,通过设施利用率、百人床位数和空间匹配度等指标,对北京市养老服务设施的规划政策进行了评估。研究表明,多智能体模拟技术对把握人口动向及养老服务需求的不确定性和动态变化特征而言是一个十分有效的研究工具,能够很好地体现各种要素的空间属性。对于北京市的“9064”养老服务规划和养老设施专项规划的分析表明,如果仅仅对养老模式的分担比例和百人床位数进行控制,而忽视对空间布局的管控,养老机构床位空置率有可能出现继续上升的趋势,为此,必须制定城市中心区养老机构的比例,同时对养老机构的定价、选址和服务质量采取必要的管控措施。  相似文献   

13.
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。  相似文献   

14.
In this article, we present a geographically explicit agent-based model (ABM), loosely coupled with vector geographical information systems (GISs), which explicitly captures and uses geometric data and socioeconomic attributes in the simulation process. The ability to represent the urban environment as a series of points, lines, and polygons not only allows one to represent a range of different-sized features such as buildings or larger areas portrayed as the urban environment but is a move away from many ABMs utilizing GIS that are rooted in grid-based structures. We apply this model to the study of residential segregation, specifically creating a Schelling (1971 Schelling, T.C. 1971. Dynamic models of segregation. Journal of Mathematical Sociology, 1(1): 143–186. [Taylor &; Francis Online] , [Google Scholar]) type of model within a hypothetical cityscape, thus demonstrating how this approach can be used for linking vector-based GIS and agent-based modeling. A selection of simulation experiments are presented, highlighting the inner workings of the model and how aggregate patterns of segregation can emerge from the mild tastes and preferences of individual agents interacting locally over time. Furthermore, the article suggests how this model could be extended and demonstrates the importance of explicit geographical space in the modeling process.  相似文献   

15.
李鲁奇  孔翔 《地理科学》2021,41(5):797-803
智能体模型用于自下而上模拟城市系统。当前综述性研究多关注其原理和缺陷等,而对研究内容演化的梳理尚不够细致。故运用主路径和冲积图分析,基于文献引用网络和关键词共现网络,梳理了国外城市系统智能体模型的研究脉络。结果表明,土地利用是核心研究领域,居住隔离、城市增长和交通等亦是重要应用主题;元胞自动机、网络分析等方法在2008年前即与该模型结合,遗传算法、大数据分析等在2016—2019年亦得到较多关注。未来可结合韧性城市、收缩城市等热点问题,以及开发区、城中村等中国特色城市问题扩展应用领域,并深化与人工智能算法和各学科传统方法的结合。  相似文献   

16.
As an important spatiotemporal simulation approach and an effective tool for developing and examining spatial optimization strategies (e.g., land allocation and planning), geospatial cellular automata (CA) models often require multiple data layers and consist of complicated algorithms in order to deal with the complex dynamic processes of interest and the intricate relationships and interactions between the processes and their driving factors. Also, massive amount of data may be used in CA simulations as high-resolution geospatial and non-spatial data are widely available. Thus, geospatial CA models can be both computationally intensive and data intensive, demanding extensive length of computing time and vast memory space. Based on a hybrid parallelism that combines processes with discrete memory and threads with global memory, we developed a parallel geospatial CA model for urban growth simulation over the heterogeneous computer architecture composed of multiple central processing units (CPUs) and graphics processing units (GPUs). Experiments with the datasets of California showed that the overall computing time for a 50-year simulation dropped from 13,647 seconds on a single CPU to 32 seconds using 64 GPU/CPU nodes. We conclude that the hybrid parallelism of geospatial CA over the emerging heterogeneous computer architectures provides scalable solutions to enabling complex simulations and optimizations with massive amount of data that were previously infeasible, sometimes impossible, using individual computing approaches.  相似文献   

17.
High performance computing has undergone a radical transformation during the past decade. Though monolithic supercomputers continue to be built with significantly increased computing power, geographically distributed computing resources are now routinely linked using high‐speed networks to address a broad range of computationally complex problems. These confederated resources are referred to collectively as a computational Grid. Many geographical problems exhibit characteristics that make them candidates for this new model of computing. As an illustration, we describe a spatial statistics problem and demonstrate how it can be addressed using Grid computing strategies. A key element of this application is the development of middleware that handles domain decomposition and coordinates computational functions. We also discuss the development of Grid portals that are designed to help researchers and decision makers access and use geographic information analysis tools.  相似文献   

18.
基于垄断竞争的大都市商业空间结构动态模拟   总被引：2，自引：1，他引：1  
薛领  翁瑾 《地理学报》2010,65(8):938-948
本文构建了一个基于垄断竞争、规模经济、交通成本、消费者多样化偏好以及商品和服务差异化的大都市两区域商业空间结构模型。提出了经济学演绎模型与基于agent 的计算实验相结合的研究路径,通过对商家、消费者等大量微观自主体(agent) 的相互作用来“动态地”观察和讨论大都市新、老城区宏观商业空间结构的微观基础、影响因素和演化过程。研究结果表明,①在商品和服务替代性、购物交通成本设定的情形下,新、老城区商业固定成本投入差距越大,则商业空间分布越不均衡,越易形成核心-边缘结构。② 由于居民的消费存在多样化偏好,因此强化区域间的差异性有助于改变商业的市场份额。③ 商业往往集聚在具有区位优势、人口规模优势以及固定成本优势的地区,而且交通条件的改善将加速商业的空间集聚。研究认为,空间经济学演绎模型与推导→基于agent 的地理计算→实证分析与计量检验是一个值得探索的技术路线。  相似文献   

19.
Performing point pattern analysis using Ripley’s K function on point events of large size is computationally intensive as it involves massive point-wise comparisons, time-consuming edge effect correction weights calculation, and a large number of simulations. This article presented two strategies to optimize the algorithm for point pattern analysis using Ripley’s K function and utilized cloud computing to further accelerate the optimized algorithm. The first optimization sorted the points on their x and y coordinates and thus narrowed the scope of searching for neighboring points down to a rectangular area around each point in estimating K function. Using the actual study area in computing edge effect correction weights is essential to estimate an unbiased K function, but is very computationally intensive if the study area is of complex shape. The second optimization reused the previously computed weights to avoid repeating expensive weights calculation. The optimized algorithm was then parallelized using Open Multi-Processing (OpenMP) and hybrid Message Passing Interface (MPI)/OpenMP on the cloud computing platform. Performance testing showed that the optimizations effectively accelerated point pattern analysis using K function by a factor of 8 using both the sequential version and the OpenMP-parallel version of the optimized algorithm. While the OpenMP-based parallelization achieved good scalability with respect to the number of CPU cores utilized and the problem size, the hybrid MPI/OpenMP-based parallelization significantly shortened the time for estimating K function and performing simulations by utilizing computing resources on multiple computing nodes. Computational challenge imposed by point pattern analysis tasks on point events of large size involving a large number of simulations can be addressed by utilizing elastic, distributed cloud resources.  相似文献   

20.
We use a GIS‐based agent‐based model (ABM), named dynamic ecological exurban development (DEED), with spatial data in hypothetical scenarios to evaluate the individual and interacting effects of lot‐size zoning and municipal land‐acquisition strategies on possible forest‐cover outcomes in Scio Township, a municipality in Southeastern Michigan. Agent types, characteristics, behavioural methods, and landscape perceptions (i.e. landscape aesthetics) are empirically informed using survey data, spatial analyses, and a USDA methodology for mapping landscape aesthetic quality. Results from our scenario experiments computationally verified literature that show large lot‐size zoning policies lead to greater sprawl, and large lot‐size zoning policies can lead to increased forest cover, although we found this effect to be small relative to municipal land acquisition. The return on land acquisition for forest conservation was strongly affected by the location strategy used to select parcels for conservation. Furthermore, the location strategy for forest conservation land acquisition was more effective at increasing aggregate forest levels than the independent zoning policies, the quantity of area acquired for forest conservation, and any combination of the two. The results using an integrated GIS and ABM framework for evaluating land‐use development policies on forest cover provide additional insight into how these types of policies may act out over time and what aspects of the policies were more influential towards the goal of maximising forest cover.  相似文献   

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