Cellular Automata (CA) Model for Primality Test

This study proposes an alternative cellular automata (CA) model, which relaxes the traditional CA regular square grid and synchronous growth, and is designed for representations of land-use change in rural-urban fringe settings. The model uses high-resolution spatial data in the form of irregularly sized and shaped land parcels, and incorporates synchronous and asynchronous development in order to model more realistically land-use change at the land parcel scale. The model allows urban planners and other stakeholders to evaluate how different subdivision designs will influence development under varying population growth rates and buyer preferences. A model prototype has been developed in a common desktop GIS and applied to a rapidly developing area of a midsized Canadian city.

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A Cellular Automata Model for Integrated Simulation of Land Use and Transport Interactions

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10030149 ◽

2021 ◽

Vol 10 (3) ◽

pp. 149

Author(s):

Nuno Pinto ◽

António P. Antunes ◽

Josep Roca

Keyword(s):

Land Use ◽

Cellular Automata ◽

Land Use Change ◽

Urban Studies ◽

Particle Swarm Algorithm ◽

Cellular Automata Model ◽

Integrated Simulation ◽

The Road ◽

Ca Model ◽

The City

Cellular automata (CA) models have been used in urban studies for dealing with land use change. Transport and accessibility are arguably the main drivers of urban change and have a direct influence on land use. Land use and transport interaction models deal with the complexity of this relationship using many different approaches. CA models incorporate these drivers, but usually consider transport (and accessibility) variables as exogenous. Our paper presents a CA model where transport variables are endogenous to the model and are calibrated along with the land use variables to capture the interdependent complexity of these phenomena. The model uses irregular cells and a variable neighborhood to simulate land use change, taking into account the effect of the road network. Calibration is performed through a particle swarm algorithm. We present an application of the model to a comparison of scenarios for the construction of a ring road in the city of Coimbra, Portugal. The results show the ability of the CA model to capture the influence of change of the transport network (and thus in accessibility) in the land use dynamics.

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A Cellular Automata Model of the Relationship between Adverse Events and Regional Infrastructure Development in an Active War Theater

Technologies ◽

10.3390/technologies7030054 ◽

2019 ◽

Vol 7 (3) ◽

pp. 54

Author(s):

Bozkurt ◽

Karwowski ◽

Çakıt ◽

Ahram

Keyword(s):

Adverse Event ◽

Cellular Automata ◽

Adverse Events ◽

Decision Makers ◽

Development Projects ◽

Infrastructure Development ◽

Complex Interactions ◽

Proposed Model ◽

Ca Model ◽

Complex Formations

This study presents a cellular automata (CA) model to assist decision-makers in understanding the effects of infrastructure development projects on adverse events in an active war theater. The adverse events are caused by terrorist activities that primarily target the civilian population in countries such as Afghanistan. In the CA-based model, cells in the same neighborhood synchronously interact with one another to determine their next states, and small changes in iteration yield to complex formations of adverse event risks. The results demonstrate that the proposed model can help in the evaluation of infrastructure development projects in relation to changes in the reported adverse events, as well as in the identification of the geographical locations, times, and impacts of such developments. The results also show that infrastructure development projects have different impacts on the reported adverse events. The CA modeling approach can be used to support decision-makers in allocating infrastructure development funds to stabilize active war regions with higher adverse event risks. Such models can also improve the understanding of the complex interactions between infrastructure development projects and adverse events.

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STABILITY ANALYSIS OF CELLULAR AUTOMATA GENERATED CLUSTERS

Mathematical Modelling and Analysis ◽

10.3846/13926292.2005.9637273 ◽

2005 ◽

Vol 12 (1) ◽

pp. 83-90

Author(s):

R. Šiugždaite

Keyword(s):

Cellular Automata ◽

Power Law ◽

State Parameter ◽

Urban System ◽

Complex Behaviour ◽

Cellular Automata Model ◽

Self Organized ◽

Tai Ji ◽

Long Time ◽

Ca Model

The development of regional urban system still remains one of the main problems during the human race history. There are a lot of problems inside this system like overcrowded cities and decaying countryside. All these situations can be reproduced by modelling them using Cellular Automata (CA) [1, 2, 5]. CA models implement algorithms with simple rules and parameter controls, but the result can be a complex behaviour. A stability of naturally formed self‐organized urban system depends on its critical state parameter τ in the power law log(f(x)) = ‐τlog(x). If the system reaches self‐organized critical (SOC) state then it remains in it for a long time. The CA model URBACAM (URBAnistic Cellular Automata Model) describes the long‐lasting term behaviour and shows that the change in behaviour is sensitive to the urban parameter τ of the power law. Regionines urbanistines sistemos vystymasis išlieka viena iš opiausiu problemu žmonijos istorijoje. Keletas tokiu uždaviniu kaip miestu perpildymas, nykstančios kaimo vietoves ir t.t. gali būti nesunkiai modeliuojami naudojant lasteliu automatus (LA). LA metodas ypatingas tuo, kad realizuoja algoritma paprastu taisykliu bei parametru valdymo pagalba, tačiau rezultate galima gauti sudetinga elgsena. Natūraliai susiformavusiu urbanistiniu sistemu stabilumas priklauso nuo sistemos krizines savirangos būsenos (KSB) parametro τ. Jei sistema pasiekia KSB, tai ji ilga laika išlieka joje. LA modelis URBACAM charakterizuoja ilgalaike elgsena ir parodo, jog modelyje jos kitimus itakoja eksponentinio desnio urbanistinis parametras τ.

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Integrating Cellular Automata with Unsupervised Deep-Learning Algorithms: A Case Study of Urban-Sprawl Simulation in the Jingjintang Urban Agglomeration, China

Sustainability ◽

10.3390/su11092464 ◽

2019 ◽

Vol 11 (9) ◽

pp. 2464

Author(s):

Cong Ou ◽

Jianyu Yang ◽

Zhenrong Du ◽

Xin Zhang ◽

Dehai Zhu

Keyword(s):

Machine Learning ◽

Deep Learning ◽

Cellular Automata ◽

Urban Sprawl ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Urban Agglomeration ◽

Unsupervised Deep Learning ◽

Ca Model ◽

Transition Rules

An effective simulation of the urban sprawl in an urban agglomeration is conducive to making regional policies. Previous studies verified the effectiveness of the cellular-automata (CA) model in simulating urban sprawl, and emphasized that the definition of transition rules is the key to the construction of the CA model. However, existing simulation models based on CA are limited in defining complex transition rules. The aim of this study was to investigate the capability of two unsupervised deep-learning algorithms (deep-belief networks, DBN) and stacked denoising autoencoders (SDA) to define transition rules in order to obtain more accurate simulated results. Choosing the Beijing–Tianjin–Tangshan urban agglomeration as the study area, two proposed models (DBN–CA and SDA–CA) were implemented in this area for simulating its urban sprawl during 2000–2010. Additionally, two traditional machine-learning-based CA models were built for comparative experiments. The implementation results demonstrated that integrating CA with unsupervised deep-learning algorithms is more suitable and accurate than traditional machine-learning algorithms on both the cell level and pattern level. Meanwhile, compared with the DBN–CA, the SDA–CA model had better accuracy in both aspects. Therefore, the unsupervised deep-learning-based CA model, especially SDA–CA, is a novel approach for simulating urban sprawl and also potentially for other complex geographical phenomena.

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Simulation of Evacuation Characteristics Using a 2-Dimensional Cellular Automata Model for Pedestrian Dynamics

Journal of Applied Mathematics ◽

10.1155/2013/284721 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 5

Author(s):

Liqiang Ji ◽

Yongsheng Qian ◽

Junwei Zeng ◽

Min Wang ◽

Dejie Xu ◽

...

Keyword(s):

Cellular Automata ◽

High Density ◽

Force Model ◽

Environment Interaction ◽

Social Force ◽

Public Places ◽

Pedestrian Dynamics ◽

Repulsion Force ◽

The People ◽

Ca Model

In public places, the high pedestrian density is one of the direct causes leading to crowding and trample disaster, so it is very necessary to investigate the collective and evacuation characteristics for pedestrian movement. In the occupants’ evacuation process, the people-people interaction and the people-environment interaction are sufficiently considered in this paper, which have been divided into the exit attraction, the repulsion force between people, the friction between people, the repulsion force between human and barrier, and the attraction of surrounding people. Through analyzing the existing models, a new occupant evacuation cellular automata (CA) model based on the social force model is presented, which overcomes the shortage of the high density crowd simulation and combines the advantages that CA has sample rules and faster calculating speed. The simulating result shows a great applicability for evacuation under the high density crowd condition, and the segregation phenomena have also been found in the bidirectional pedestrian flow. Besides these, setting isolated belt near the exit or entrance of underpass not only remarkably decreases the density and the risk of tramper disaster but also increases the evacuation efficiency, so it provides a new idea for infrastructure design about the exits and entrances.

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Can CA describe collective effects of polluting agents?

International Journal of Modern Physics C ◽

10.1142/s0129183115501144 ◽

2015 ◽

Vol 26 (10) ◽

pp. 1550114 ◽

Cited By ~ 1

Author(s):

A. Troisi

Keyword(s):

Cellular Automata ◽

Urban Growth ◽

Formal Model ◽

Dynamical Evolution ◽

Collective Effects ◽

Simulation Tool ◽

Combined Effects ◽

Competitive Effects ◽

Ca Model ◽

Previous Algorithm

Pollution represents one of the most relevant issues of our time. Several studies are on stage but, generally, they do not consider competitive effects, paying attention only to specific agents and their impact. In this paper, it is suggested a different scheme. At first, it is proposed a formal model of competitive noxious effects. Second, by generalizing a previous algorithm capable of describing urban growth, it is developed a cellular automata (CA) model that provides the effective impact of a variety of pollutants. The final achievement is a simulation tool that can model pollution combined effects and their dynamical evolution in relation to anthropized environments.

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THE CARRYING CAPACITY UNDER FOUR-ASPECT COLOR LIGHT AUTOMATIC BLOCK SIGNALING BASED ON CELLULAR AUTOMATA

Modern Physics Letters B ◽

10.1142/s0217984913500905 ◽

2013 ◽

Vol 27 (13) ◽

pp. 1350090 ◽

Cited By ~ 5

Author(s):

YUAN XUE ◽

YONG-SHENG QIAN ◽

XIAO-PING GUANG ◽

JUN-WEI ZENG ◽

ZHI-LONG JIA ◽

...

Keyword(s):

Control System ◽

Cellular Automata ◽

Carrying Capacity ◽

Dynamic Control ◽

Signal Control ◽

Cellular Automata Model ◽

Railway Signal ◽

Control Pattern ◽

Train Speed ◽

Ca Model

With the application of the dynamic control system, Cellular Automata model has become a valued tool for the simulation of human behavior and traffic flow. As an integrated kind of railway signal-control pattern, the four-aspect color light automatic block signaling has accounted for 50% in the signal-control system in China. Thus, it is extremely important to calculate correctly its carrying capacity under the automatic block signaling. Based on this fact the paper proposes a new kind of "cellular automata model" for the four-aspect color light automatic block signaling under different speed states. It also presents rational rules for the express trains with higher speed overtaking trains with lower speed in a same or adjacent section and the departing rules in some intermediate stations. In it, the state of mixed-speed trains running in the section composed of many stations is simulated with CA model, and the train-running diagram is acquired accordingly. After analyzing the relevant simulation results, the needed data are achieved herewith for the variation of section carrying capacity, the average train delay, the train speed with the change of mixed proportion, as well as the distance between the adjacent stations.

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A STUDY OF DYNAMIC RECRYSTALLIZATION IN TA15 TITANIUM ALLOY DURING HOT DEFORMATION BY CELLULAR AUTOMATA MODEL

International Journal of Modern Physics B ◽

10.1142/s0217979209060269 ◽

2009 ◽

Vol 23 (06n07) ◽

pp. 934-939 ◽

Cited By ~ 2

Author(s):

DONG HE ◽

JING CHUAN ZHU ◽

YANG WANG ◽

YONG LIU

Keyword(s):

Titanium Alloy ◽

Flow Stress ◽

Dislocation Density ◽

Cellular Automata ◽

Dynamic Recrystallization ◽

Strain Rate ◽

Hot Deformation ◽

Temperature Filed ◽

Ca Model ◽

Grain Growth Model

The dynamic recrystallization (DRX) of TA 15 ( Ti -6 Al -2 Zr -1 Mo -1 V ) titanium alloy during the hot deformation process was studied by the Cellular Automata (CA) model which is base on the dislocation density theory. To build the CA model, the dislocation density model, dynamic recovery model, nucleation model and grain growth model were introduced and developed. The influences of strain rate on the microstructure evolution and flow stress character were investigated which shows that high strain rate leads to later DRX appearance, high flow stress peak value, small mean size of recrystallizing grains( R -grains) and low DRX percentage, but they have the similar Avrami curve. The characteristic of DRX process in a modeling non-uniform temperature filed (NTF) has been studied. All the simulation results show good agreement with the pioneer's work and experimental results.

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Quick and accurate Cellular Automata sewer simulator

Journal of Hydroinformatics ◽

10.2166/hydro.2014.070 ◽

2014 ◽

Vol 16 (6) ◽

pp. 1359-1374 ◽

Cited By ~ 8

Author(s):

Rebecca J. Austin ◽

Albert S. Chen ◽

Dragan A. Savić ◽

Slobodan Djordjević

Keyword(s):

Cellular Automata ◽

Real Time ◽

Flow Conditions ◽

Computationally Efficient ◽

Real Time Control ◽

Time Control ◽

Ca Model ◽

Control Of Networks ◽

Expensive Model

As urbanisation and climate change progress, the frequency of flooding will increase. Each flood event causes damage to infrastructure and the environment. It is thus important to minimise the damage caused, which can be done through planning for events, real-time control of networks and risk management. To perform these actions, many different simulations of network behaviour are required involving complex and computationally expensive model runs. This makes fast (i.e. real-time or repetitive) simulations very difficult to carry out using traditional methods, thus there is a requirement to develop computationally efficient and accurate conceptual sewer simulators. A new Cellular Automata (CA) based sewer model is presented which is both fast and accurate. The CA model is Lagrangian in nature in that it represents the flow as blocks, and movement of the blocks through the system is simulated. To determine the number of blocks which should be moved it uses either the Manning's or Hazen–Williams equation depending on the flow conditions to calculate the permitted discharge. A case study of the sewer network in Keighley, Yorkshire, is carried out showing its performance in comparison to traditional sewer simulators. The benchmarks used to verify the results are SIPSON and SWMM5.

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