基于元胞自动机模型的图像分割算法

针对图像处理中的图像分割任务,我们提出了一个基于模糊元胞自动机模型的图像分割算法.将元胞自动机原理中的演化规则换为模糊规则建立模糊元胞自动机模型,使图像中灰度水平介于目标和背景之间的像素得以更好地归类,从而得到较好的图像分割结果.     

基于元胞自动机的SARS传播模型

根据SARS的局部性、潜伏性特征以及传染病个体传播的特点,人群接触通过近距离邻居发生,利用元胞自动机模型时间、空间上离散,以局部规则为基础,以同步更新为前提讨论整体性质的机制,将人群分为易感者,带菌者,病人,免疫者之后,以易感者对SARS的抵抗能力、病人或带菌者对SARS的传染能力、人群的大小为参数,建立了基于元胞自动机的SARS传播模型.得到的结果可为从传染动力学角度控制SARS的传播提供依据.     

建立在模糊逻辑上的模糊元胞自动机

总结了经典元胞自动机模型理论,并在此基础上把模糊逻辑引入元胞自动机模型中.通过对模糊元胞自动机的基本原理的分析,定义了模糊元胞自动机模型.模糊元胞自动机模型可以处理模糊信息,并且使模拟与现实世界的情况更为接近.     

基于元胞自动机的供需网企业合作驱动建模与仿真

针对供需网企业合作驱动具有一定的复杂性这一现状,基于元胞自动机模型对三种状态的节点交互及供需网系统合作演变过程进行仿真,探讨了不同驱动作用下供需网企业合作行为的演化趋势。研究结果表明:供需网企业合作行为演化存在供需质交互频率阈值,当交互频率大于该阈值时,企业合作数量较高且会稳定在某一水平;提高企业的多功能合作执行力、外部力量等可以增加企业合作规模和数量,进而可以促进合作子系统的形成和合作平台的构建。     

场馆人员疏散的元胞自动机模拟

在人口密集场所(馆)观众席位区及疏散通道分布模拟图的基础上,应用数据库技术结合元胞自动机模拟了场馆中人员的疏散情况,并针对场馆发生突发事件后,在疏散过程中某个出口堵塞的情形进行了模拟,模拟结果可以记录人员疏散的轨迹,为突发事件发生后人员疏散应急方案提供参考.     

基于元胞自动机的交叉口混合交通模型研究

在我国很多中小城市普遍存在着摩托车与小汽车混行的现象,摩托车既有类似自行车横向移动灵活、启动速度快的特点,又有类似小汽车纵向移动速度快的特点,特别是在城市交叉口附近范围内,摩托车与小汽车几乎速度相当.根据交叉口红灯起亮时,摩托车会灵活穿插,充分利用车道空间,绿灯起亮时,由于摩托车的启动速度比小汽车快,产生侧向膨胀效应,挤压小汽车行驶空间,从而使其速度减慢等现象,结合我国中小城市交叉口小汽车及摩托车的行驶特性,利用元胞自动机模型,建立信号交叉口小汽车与摩托车的混合交通模型.     

基于二型模糊逻辑的元胞自动机模型

将二型模糊逻辑推理引入到元胞自动机模型中,把二型模糊逻辑推理与经典的元胞自动机模型结合起来,建立一种新的推理演化模型,基于二型模糊逻辑的元胞自动机模型.元胞自动机模型的关键部分是演化规则和元胞状态.将元胞自动机模型中的演化规则二型模糊化,将经典元胞自动机模型中的元胞状态模糊化为二型模糊状态,建立基于二型模糊逻辑的元胞自动机模型.     

22号初等元胞自动机的演化复杂性

Cellular automata are the discrete dynamical systems of simple construction but with complex and varied behaviors. In this paper, the elementary cellular automaton of rule 22 is studied by the tools of formal language theory and symbolic dynamics. Its temporal evolution orbits are coarse-grained into evolution sequences and the evolution languages are defined. It is proved that for every n≥2 its width n evolution language is not regular.     

基于跟车思想的一维元胞自动机交通流模型

提出一个改进的一维元胞自动机模型来模拟周期性边界条件下高速公路上车流运动.基于跟车模型的思想,根据所研究车辆与其前方紧邻车辆之间的间距和相对速度来确定该车的运动,间接地反映了次近邻车辆的影响.通过引入安全间距来描述高速运动车辆接近前方缓行车辆时的减速行为,并利用随机减速概率来反映减速行为中的随机因素.由于安全间距的引入,当减速概率大于零时在较高密度下就出现完全的阻塞相.同时在本模型中采用的是有条件减速,因而可以较好描述交通实测中观察到的现象.在临界密度附近,车流运动处于亚稳态并呈现出滞后现象.由于本模型对于车辆微观运动的合理描述,可以直接用以研究在交通灯控制下城市道路交通中的各种现象.     

随机化交通灯的二维元胞自动机交通模型

元胞自动机交通模型以简单的规则反映交通系统中的多种因素，可以分析各种交通现象，且可在计算机上方便、高效地运作·Ｂｉｈａｍ－Ｍｉｄｄｌｅｔｏｎ－Ｌｅｖｉｎｅ模型（ＢＭＬ模型）实现了二维交通问题的元胞自动机模型的模拟研究·本文对ＢＭＬ模型作了改进，解除了该模型中关于交通灯同步变化的限制·在新模型中，每个路口的交通灯可以自由选定起始工作时间和变化节奏，于是可以更全面、准确地反映交通灯对交通系统性能的影响·本文还对新模型中出现的若干新效应作了解释·     

Guidelines for dynamics‐based parameterization of one‐dimensional cellular automata rule spaces

As paradigmatic complex systems, various studies have been done in the context of one‐dimensional cellular automata (CA) on the definition of parameters directly obtained from their transition rule, aiming at the help they might provide to forecasting CA dynamic behavior. Out of the analysis of the most important parameters available for this end, as well as others evaluated by us, a set of guidelines is proposed that should be followed when defining a parameter of that kind. Based upon the guidelines, a critique of those parameters is made, which leads to a set of five that jointly provide a good forecasting set; two of them were drawn from the literature and three are new ones defined according to the guidelines. By using them as a heuristic in the evolutionary search for CA of a predefined computational behavior, good results have been obtained, exemplified herein by the evolutionary search for CA that perform the Synchronization Task. © 2001 John Wiley & Sons, Inc.     

Control parameters in Boolean networks and cellular automata revisited from a logical and a sociological point of view

The use of “control parameters” as applied to describe the dynamics of complex mathematical systems within models of real social systems is discussed. Whereas single control parameters cannot sufficiently characterize the dynamics of such systems it is suggested that domains of values of certain sets of parameters are appropriately denoting necessary conditions for highly disordered dynamics of social systems. Various of those control parameters permit a straightforward interpretation in terms of properties of social rules and structures. © 1999 John Wiley & Sons, Inc.     

Is prediction possible? Chaotic behavior of Multiple Equilibria Regulation Model in cellular automata topology

In this article, we present the Multiple Equilibria Regulation (MER) Model in cellular automata topology. As argued in previous explorations of the model, for certain parameter values, the behavior of the system exhibits transient chaos (namely, the system is unpredictable but ends in a final steady state). In order to approach empirical reality, we introduce a cellular automata topology. Examining the outcome of the simulations leads us to conclude that for certain parameter values tested, the system yields chaotic behavior. Thus, cellular automata contribution has proven crucial, because the introduced topology converts the behavior of the system from transient chaos to “pure” chaos, i.e., the system is not only unpredictable on the long run but, in addition, it will never rest in a final steady state. According to these findings, authors argue the theoretical hypothesis that the urge for “prediction” in social sciences should be reconsidered in terms of “predictability horizon”. © 2004 Wiley Periodicals, Inc. Complexity 10: 23–36, 2004     

Three-dimensional cellular automaton simulation of tumour growth in inhomogeneous oxygen environment

Cellular automaton theory has previously been used to study cell growth. In this study, we present a three-dimensional cellular automaton model performing the growth simulation of normal and cancerous cells. The necessary nutrient supply is provided by an artificial arterial tree which is generated by constrained constructive optimization. Spatial oxygen diffusion is approximated again by a cellular automaton model. All results could be illustrated dynamically by three-dimensional volume visualization. Because of the chosen modelling approach, an extension of the model to simulate angiogenic processes is possible.     

Classifying cellular automata automatically: Finding gliders,filtering, and relating space‐time patterns,attractor basins,and the Z parameter

Cellular automata (CA) rules can be classified automatically for a spectrum of ordered, complex, and chaotic dynamics by a measure of the variance of input‐entropy over time. Rules that support interacting gliders and related complex dynamics can be identified, giving an unlimited source for further study. The distribution of rule classes in rule‐space can be shown. A byproduct of the method allows the automatic “filtering” of CA space‐time patterns to show up gliders and related emergent configurations more clearly. The classification seems to correspond to our subjective judgment of space‐time dynamics. There are also approximate correlations with global measures on convergence in attractor basins, characterized by the distribution of in‐degree sizes in their branching structure, and to the rule parameter, Z. Based on computer experiments using the software Discrete Dynamics Lab (DDLab), this article explains the methods and presents results for 1D CA. © 1999 John Wiley & Sons, Inc.     

Low‐density barriers for controlling plant crowd diseases: How far and fast can pathogens spread?

We explore numerically the possibility of controlling the spread of plant diseases characterized by relatively low dispersal (crowd diseases) through the introduction of a spatial barrier with low density of susceptible hosts. We use the diffusion approximation to Kendall's spatially extended version of the Kermack–McKendrick epidemic model and illustrate our findings within the context of a representative viral disease that affects cocoa trees. RECOMMENDATIONS FOR MANAGERS:

• Our numerical results suggest that using low‐density barriers of hosts in crowd plant diseases might be an effective way of halting the spatial dispersal of pathogens. The introduction of these barriers may reduce the economic impact when compared with other methods of controlling the disease spread.
• Before using the model to approximate suitable sizes of barriers, it is necessary to execute an exhaustive assessment of the model appropriateness for any particular disease under consideration.
• Our results suggest that to improve the efficiency of low‐density barriers it is important to explore their use in combination of current alternative control methods.

     

A cellular automata model of chemotherapy effects on tumour growth: targeting cancer and immune cells

The effects of therapy on avascular cancer development based on a stochastic cellular automata model are considered. Making the model more compatible with the biology of cancer, the following features are implemented: intrinsic resistance of cancerous cells along with drug-induced resistance, drug-sensitive cells, immune system. Results are reported for no treatment, discontinued treatment after only one cycle of chemotherapy, and periodic drug administration therapy modes. Growth fraction, necrotic fraction, and tumour volume are used as output parameters beside a 2-D graphical growth presentation. Periodic drug administration is more effective to inhibit the growth of tumours. The model has been validated by the verification of the simulation results using in vivo literature data. Considering immune cells makes the model more compatible with the biological realities. Beside targeting cancer cells, the model can also simulate the activation of the immune system to fight against cancer.

Abbreviations CA: cellular automata; DSC: drug sensitive cell; DRC: drug resistant cell; GF: growth fraction; NF: necrotic fraction; ODE: ordinary differential equation; PDE: partial differential equation; SCAM: The proposed stochastic cellular automata model