Construction,mathematical description and coding of reactive lattice-gas cellular automaton

We construct a reactive lattice-gas cellular automaton (LGCA) for reaction–diffusion systems and provide extensive discussion of its software coding aspects. The software coding aspects provide rationale for some choices in the construction of LGCA which has been inspired by molecular dynamics. Portability of the C language source code, of the data structures, and of the data formats is discussed and explained. We illustrate the ideas behind the development of LGCA and its code by considering a particular reacting system, the Sel'kov model with immobile complexing species. We demonstrate usefulness of LGCA modelling of reactive systems by presenting various simulation results. We compare these results with the standard numerical simulations of reaction–diffusion equations. We conclude the paper by discussing how LGCA methodology can be applied and extended to other contexts.     

Spatio-temporal organization of a cellular automaton model for computer network

It was unveiled by Ren et al. [Comput. Phys. Comm. (2001)] that congestion transition emerges in cellular automaton models for computer network and this NaSch network model with Q=1 has similar behaviours as the NaSch traffic model with maximum velocity v_max=1. For these two NaSch models, the main difference lies in a node cell contained in the NaSch network model. In this paper, we will focus on our further investigation on spatio-temporal organization of the NaSch network model. More interesting phenomena of phase transition are discovered. Firstly, fundamental diagram illustrates that when Q>1 for the NaSch network model it is significantly different from its counterpart, i.e. the NaSch traffic model in a road traffic system. The addition of a node cell, which is allowed to have more than one packets, will lead to generating a new phase. Secondly, in order to characterize phase transition occurred in the NaSch network model, an order parameter is presented with the use of the time average density of nearest-neighbor pairs m. The computational results obtained show that criticality will disappear in a strict sense if noise exists. Finally, two other numerical features, i.e. spatial correlation functions G(r) and relaxation times τ, are analyzed so as to deeply describe behaviours near critical points.     

A simplified combat model based on a cellular automaton

The work is devoted to constructing a cellular automaton based model of motion and combat activity of systems of hierarchically organized agents with allowance for terrain ruggedness, communication channels between the agents, and the necessity of choosing behavior adequate to the current situation.     

Analysis of a cellular automaton model for car traffic with a slow-to-stop rule

We propose a modification of the widely known Benjamin–Johnson–Hui (BJH) cellular automaton model for single-lane traffic simulation. In particular, our model includes a ‘slow-to-stop’ rule that exhibits more realistic microscopic driver behaviour than the BJH model. We present some statistics related to fuel economy and pollution generation and show that our model differs greatly in these measures. We give concise results based on extensive simulations using our system.     

行人交通微观动态元胞自动机仿真模型研究

在分析行人交通特性后,以元胞自动机（CA）和规则描述为理论基础,提出基于CA的行人仿真模型,以此建立相对于其他交通对象的行人避让模型。该方法以模型与现实世界的高相似性有效克服了精确数学模型在仿真行人交通时的难题。结合行人CA模型和行人避让模型开发了混合交通流仿真试验原型系统。仿真结果表明,该方法有效地模拟了现实交通状况,在城市交通规划、交通需求管理和交通控制等领域有着广泛的应用前景。     

一种自组织的二维元胞自动机网络模型及分析

提出了一种自组织的二维元胞自动机网络模型,并研究了网络中的临界特征和长相关特性。模型中,每个元胞包含一个路由器和随机数目的终端,并且能独立地根据探测到的网络拥塞状况调节其终端的数据包发送速率。仿真结果表明,在拥塞控制机制的作用下,网络能自组织地工作在临界状态,虽然节点间呈现出明显的异构特征,但节点数据包排队长度在时间和空间上仍都表现出较强的相关性。     

一种改进的NS元胞自动机模型

研究改进了基于元胞自动机的一维NS交通模型，细化了元胞长度和时间步长，对静止车辆的加速能力进行了约束，用简单的方法解决了该模型中车辆的速度演化规则与前车速度无关的缺点。同时，考虑了交通密度对随机慢化概率的影响。计算机仿真表明：改进模型不仅得到了一些与其他元胞自动机模型共有的性质，且得到的基本图更加接近实测数据。     

Automatically obtaining a cellular automaton scheme for modeling protein folding using the FCC model

This paper proposes to model protein folding as an emergent process, using machine learning to infer the folding modeling only from information of known protein structures. Using the face-centered cubic lattice for protein conformation representation, the dynamic nature of protein folding is captured with an evolved neural cellular automaton that defines the amino acids moves along the protein chain and across time. The results of the final folded conformations are compared, using different protein benchmarks, with other methods used in the traditional protein structure prediction problem, highlighting the capabilities and problems found with this modeling.

     

CURIE: a cellular automaton for concept drift detection

Data Mining and Knowledge Discovery - Data stream mining extracts information from large quantities of data flowing fast and continuously (data streams). They are usually affected by changes in the...     

A cellular automaton model of particle motions and its applications

A natural object such as a flame with smoke is featured in terms of ambiguous boundaries and complex motion. One way of modeling natural objects is by particle systems, which need a large amount of computation time to calculate interactions among the particles. This paper deseribes another way of modeling particle motions based on a cellular automaton. Cellular automata are massively parallel computation models that can simulate complex phenomena. In our model, particle motions are simulated in a cellular space with a Margolus neighborhood, which has good conservation properties and collision detectability. This paper shows several applications in two-dimensional cellular space.     

Halting the hallmarks: a cellular automaton model of early cancer growth inhibition

Cancer treatment is a fragmented and varied process, as “cancer” is really hundreds of different diseases. The “hallmarks of cancer” proposed by Hanahan and Weinberg (Cell 100(1):57–70, 2000) are a framework for viewing cancer within a common set of underlying principles—ten properties that are common to almost all cancers, allowing them to grow uncontrollably and ravage the body. We used a cellular automaton model of tumour growth paired with lattice Boltzmann methods modelling oxygen flow to simulate combination drugs targeted at knocking out pairs of hallmarks. We found that knocking out some pairs of cancer-enabling hallmarks did not prevent tumour formation, while other pairs significantly prevent tumour growth (\(p=0.0004\) using Wilcoxon signed-rank adjusted with the Bonferroni correction for multiple comparisons). This is not what would be expected from models of knocking out the hallmarks individually, as many pairs did not have an additive effect but had either no statistically significant effect or a multiplicative one. We propose that targeting certain pairs of cancer hallmarks, specifically cancers ability to induce blood vessel development paired with another cancer hallmark, could prove an effective cancer treatment option.     

Offset control of traffic signal using cellular automaton traffic model

This paper deals with an offset control of traffic signals using a cellular automaton traffic model. A stochastic optimal control method for distributed traffic signals is modified to achieve coordinated traffic signal control with the proposed offset control method. In the proposed coordinated traffic signal control method, splits of each cycle and common cycle length are calculated using a modified stochastic optimal control method, and then the offset is calculated using an estimation method based on a modified CA traffic model at intervals. Also, simulations are carried out at multiple intersections using a micro traffic simulator. The effectiveness of the proposed coordinated control method is proved by comparing with other traffic signal control methods such as pre-timed signal control, two types of the traditional coordinated control and distributed control.     

大型客车影响的双车道多速混合交通流CA模型研究

在对现有经典交通流元胞自动机模型进行总体分析的基础上,结合我国高速公路特点,通过重新标定元胞长度、运行车速、随机慢化机制,制定车道转换规则,构建了周期边界条件下考虑大型客车影响的双车道多速混合交通流元胞自动机模型,并通过计算机模拟分析了速度、密度、流量三参数之间关系,寻找出了大型客车占有率、大型客车随机慢化概率、变换车道车辆数等因素对交通流的影响规律,为合理的组织高速公路交通管理提供了理论依据。     

基于元胞自动机模型的交通流混沌仿真研究

研究一维元胞自动机模型——Nagel-Schreckenberg（NS）模型的交通流混沌问题。用Matlab程序产生交通流时间序列,在一定参数组合情况下,仿真研究了交通流车队中前后车辆之间车头间距的变化过程,并在此基础上讨论了车辆密度和车辆减速概率的变化对交通流运动状态的影响。结果表明,当车流密度超过某一值时,NS模型仿真出的交通流会产生混沌现象;而交通流混沌产生的根本原因在于交通流的内在随机性,其中车辆不规则的加速、减速是这种内在随机性的主要因素。     

On the hierarchy of conservation laws in a cellular automaton

Conservation laws in cellular automata (CA) are studied as an abstraction of the conservation laws observed in nature. In addition to the usual real-valued conservation laws we also consider more general group-valued and semigroup-valued conservation laws. The (algebraic) conservation laws in a CA form a hierarchy, based on the range of the interactions they take into account. The conservation laws with smaller interaction ranges are the homomorphic images of those with larger interaction ranges, and for each specific range there is a most general law that incorporates all those with that range. For one-dimensional CA, such a most general conservation law has—even in the semigroup-valued case—an effectively constructible finite presentation, while for higher-dimensional CA such effective construction exists only in the group-valued case. It is even undecidable whether a given two-dimensional CA conserves a given semigroup-valued energy assignment. Although the local properties of this hierarchy are tractable in the one-dimensional case, its global properties turn out to be undecidable. In particular, we prove that it is undecidable whether this hierarchy is trivial or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. In particular, we show that positively expansive CA do not have non-trivial real-valued conservation laws.     

基于元胞自动机模型的交织区车道分配问题分析

为探究交织区不同车道分配方案对系统产生的影响效果,在Nagel和Schreckenberg提出的NS元胞自动机模型的基础上为三种不同换道区域定义了三种换道规则,建立针对交织区的元胞自动机模型。对比交织区是否设置隔离带的两种车道分配情况下交织区及非交织区分别进行了数值的模拟和分析,结果表明,流量低时,两种措施的效果无明显差异;流量较高并且交织比不大时设置隔离带将减少系统拥堵及各流向车辆的行程时间。当交织区的长度在一定值内,设置隔离带的效果更好,且随着交织区长度的增加,设置隔离带而产生的优化效果也越来越小。交织区超过这个长度后两种措施效果差不多。     

Large-scale parallel lattice Boltzmann–cellular automaton model of two-dimensional dendritic growth

An extremely scalable lattice Boltzmann (LB)–cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid–liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites.