A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology

Cellular automata (CA) models can simulate complex urban systems through simple rules and have become important tools for studying the spatio-temporal evolution of urban land use. However, the multiple and large-volume data layers, massive geospatial processing and complicated algorithms for automatic calibration in the urban CA models require a high level of computational capability. Unfortunately, the limited performance of sequential computation on a single computing unit (i.e. a central processing unit (CPU) or a graphics processing unit (GPU)) and the high cost of parallel design and programming make it difficult to establish a high-performance urban CA model. As a result of its powerful computational ability and scalability, the vectorization paradigm is becoming increasingly important and has received wide attention with regard to this kind of computational problem. This paper presents a high-performance CA model using vectorization and parallel computing technology for the computation-intensive and data-intensive geospatial processing in urban simulation. To transfer the original algorithm to a vectorized algorithm, we define the neighborhood set of the cell space and improve the operation paradigm of neighborhood computation, transition probability calculation, and cell state transition. The experiments undertaken in this study demonstrate that the vectorized algorithm can greatly reduce the computation time, especially in the environment of a vector programming language, and it is possible to parallelize the algorithm as the data volume increases. The execution time for the simulation of 5-m resolution and 3 × 3 neighborhood decreased from 38,220.43 s to 803.36 s with the vectorized algorithm and was further shortened to 476.54 s by dividing the domain into four computing units. The experiments also indicated that the computational efficiency of the vectorized algorithm is closely related to the neighborhood size and configuration, as well as the shape of the research domain. We can conclude that the combination of vectorization and parallel computing technology can provide scalable solutions to significantly improve the applicability of urban CA.     

A Time Monte Carlo method for addressing uncertainty in land-use change models

One of the main objectives of land-use change models is to explore future land-use patterns. Therefore, the issue of addressing uncertainty in land-use forecasting has received an increasing attention in recent years. Many current models consider uncertainty by including a randomness component in their structure. In this paper, we present a novel approach for tuning uncertainty over time, which we refer to as the Time Monte Carlo (TMC) method. The TMC uses a specific range of randomness to allocate new land uses. This range is associated with the transition probabilities from one land use to another. The range of randomness is increased over time so that the degree of uncertainty increases over time. We compare the TMC to the randomness components used in previous models, through a coupled logistic regression-cellular automata model applied for Wallonia (Belgium) as a case study. Our analysis reveals that the TMC produces results comparable with existing methods over the short-term validation period (2000–2010). Furthermore, the TMC can tune uncertainty on longer-term time horizons, which is an essential feature of our method to account for greater uncertainty in the distant future.     

基于影响因子动态更新的都市圈国土-人口协同模拟

都市圈作为典型的复杂巨系统,其国土、人口、交通等要素呈现出共同演化、协同发展的特征。现有基于元胞自动机的空间模拟方法通常分别进行国土或人口模拟,忽略了国土、人口之间的协同演化,从而限制了模拟性能。本文提出一种影响因子动态更新策略用以表征国土、人口两种要素间的相互作用,拓展经典元胞自动机模型构建协同模拟算法,实现了都市圈国土与人口空间分布态势的精准模拟。本文以深莞惠都市圈为例,对提出算法进行了实验验证。实验结果表明,本文提出协同模拟算法在深莞惠都市圈的国土模拟品质因素为0.274、人口模拟平均绝对百分比误差23.55%,分别优于传统基于随机森林的元胞自动机算法0.24和29.33%;相较于传统模型,在国土模拟中本模型在对于建设用地的模拟准确度提升了约3%,在人口模拟中本模型在对人口高密度的区域模拟误差降低了约6%。本文进一步预测了深莞惠都市圈2030年国土和人口发展空间态势。研究结果可为都市圈重大基础设施选址和发展情景推演提供技术支撑。     

用于地震波场模拟的变网格边长声格固体模型

提出一种新的用于地震波场模拟的变网格边长声格固体模型（Phononiclatticesolidwithvariousgridlength,简称PLSVL模型）．该模型通过改变不同介质中网格的边长来体现介质速度的变化,粒子在所有网格中的运动均保持每一步运行一个网格边长．详细推导了该模型的Boltzmann方程,证明该方程及其散射项的表达式与PLS模型相同,因而从该方程出发,可寻出宏观变量所满足的波动方程．新模型在同种网格内部的传输过程不存在误差,在界面产生的误差不会随时间而积累．本文同时给出了一个理论模型的波场模拟结果．     

细胞自动机地震波模拟的并行化算法

采用区域分解的办法对格子气自动机地震波传播模拟的并行化算法进行了研究,提出了两种区域分解算法,并在SGIPowerChallenge并行计算机上进行了实际地质模型中平面波反射地震响应的计算,获得了较高的并行计算效率．     

土地利用变化研究中的细胞自动机与灰色局势决策

把细胞自动机和灰色局势决策结合起来对土地利用变换机制进行模拟。实验证明,基于灰色局势决策规则的细胞自动机是对土地利用变换机制从宏观和微观角度进行模拟的有效方法。     

Developing land use scenario dynamics model by the integration of system dynamics model and cellular automata model

Models of land use change are useful tools for un-derstanding the analysis of the cause and conse-quences of land use changes, assessing the impacts of land use system on ecological system and supporting land use planning and policy[1,2]. Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are regarded as one of the good ways to un-derstand the interactive mechanism between land use system and ecological system[3―10…     

Archaea,the tree of life,and cellular evolution in eukaryotes

The early history of life harbours many unresolved evolutionary questions, none more important than the genomic origin and cellular evolution of eukaryotes. An issue central to eukaryote origin concerns the position of eukaryotes in the tree of life and the relationship of the host lineage that acquired the mitochondrion some two billion years ago to lineages of modern-day archaea. Recent analyses indicate that the host lineage branches within the Archaea, prompting the search for novel archaeal lineages that can improve our understanding of the cellular evolution of eukaryotes. Here we give a brief review of the studies on Archaea, the tree of life and the cellular evolution of eukaryotes, which is followed by an overview of recent progress fueled by new genomic technologies and recent status of archaeal research in China. Future directions for the study of early evolution are considered.     

On-chip earthquake simulation model using potentials

A two-dimensional (2-D) Cellular Automata (CA) dynamic system constituted of cells-charges has been proposed for the simulation of the earthquake process. The CA model has been calibrated with the use of real data. The calibration incorporates major seismic characteristics of the area under test. The simulation results are found in good quantitative and qualitative agreement with the recorded Gutenberg–Richter (GR) scaling relations. The model is enriched with a powerful multi-parameter interface that enables the user to load real data from different regions. This paper examines the on-chip realisation of the model and its instrumentation. The CA model hardware implementation is based on Field Programmable Gate Array (FPGA) logic. It utilises an array of 32 × 32 cells. Parameters that construct the local CA rule constitute the input data. The initial seed, which to some extent corresponds to the seismic features of the area under test, is loaded in a semi-parallel way and the process is completed in a certain number of time steps. The automatic response of the processor provides the corresponding GR scaling law of the area under study. The hardware implementation of the CA-based earthquake simulation model is advantageous in terms of low-cost, high-speed, compactness and portability features. It can operate as a preliminary data-acquisition filter that accelerates the evaluation of recorded data as far as its origin time, spatial and magnitude completeness and quality are concerned. Software that performs reliable automatic phase picking, as well as data elaboration, can be assembled next to the earthquake recording instruments (the whole network) output to assure a quick and reliable iteration of the focal parameters of a recorded earthquake (epicentre coordinates, focal depth and magnitude). The dedicated processor can be accommodated right after this stage (before any manual elaboration) focusing on the near real-time development of a reliable qualitative dynamical seismic record and a mapping of the seismic characteristics of the area.     

细胞自动机用于地震偏移:数值模拟试验

利用细胞自动机模型进行了地震偏移处理的尝试．采用格子Boltzmann模型和三角形网格,以向下两个方向的粒子代表下行波,根据归一化的地震记录计算粒子数密度,在相应的时刻在代表地表的网格点上设定粒子数密度,以下行粒子在网格中的演化模拟波场延拓过程．粒子系统演化结束时即得到偏移后的波场图象．本文对一个常速介质理论模型进行了偏移处理,得到了满意的结果。