Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban growth and future scenarios in global arid areas such as Northwest China and Africa.

A cellular automata framework for porous electrode reconstruction and reaction-diffusion simulation

Due to the high charge transfer efficiency compared to that of non-porous materials,porous electrodes with larger surface area and thinner solid pore walls have been widely applied in the lithium-ion battery field.Since the capacity and charge-discharge efficiency of batteries are closely related to the microstructure of porous materials,a conceptually simple and computationally efficient cellular automata(CA)framework is proposed to reconstruct the porous electrode structure and simulate the reactiondiffusion process under the irregular solid-liquid boundary in this work.This framework is consisted of an electrode generating model and a reaction-diffusion model.Electrode structures with specific geometric properties,i.e.,porosity,surface area,size distribution,and eccentricity distribution can be constructed by the electrode generating model.The reaction-diffusion model is exemplified by solving the Fick's diffusion problem and simulating the cyclic voltammetry(CV)process.The discharging process in the lithium-ion battery are simulated through combining the above two CA models,and the simulation results are consistent with the well-known pseudo-two-dimensional(P2D)model.In addition,a set of electrodes with different microstructures are constructed and their reaction efficiencies are evaluated.The results indicate that there is an optimum combination of porosity and particle size for discharge efficiency.This framework is a promising one for studying the effect of electrode microstructure on battery performance due to its fully synchronous computation way,easy handled boundary conditions,and free of convergence concerns.

Optimization of desert lake information extraction from remote sensing images using cellular automata

Desert lakes are important wetland resources in the blown-sand area of western China and play a significant role in maintain-ing the regional ecological environment.However,large-scale coal mining in recent years has considerably impacted the deposition condition of several lakes.Rapid and accurate extraction of lake information based on satellite images is crucial for developing protective measures against desertification.However,the spatial resolution of these images often leads to mixed pixels near water boundaries,affecting extraction precision.Traditional pixel unmixing methods mainly obtain water coverage information in a mixed pixel,making it difficult to accurately describe the spatial distribution.In this paper,the cellular automata(CA)model was adopted in order to realize lake information extraction at a sub-pixel level.A mining area in Shenmu City,Shaanxi Province,China is selected as the research region,using the image of Sentinel-2 as the data source and the high spatial resolution UAV image as the reference.First,water coverage of mixed pixels in the Sentinel-2 image was calculated with the dimidiate pixel model and the fully constrained least squares(FCLS)method.Second,the mixed pixels were subdivided to form the cellular space at a sub-pixel level and the transition rules are constructed based on the water coverage information and spatial correlation.Lastly,the process was implemented using Python and IDL,with the ArcGIS and ENVI software being used for validation.The experiments show that the CA model can improve the sub-pixel positioning accuracy for lake bodies in mixed pixel image and improve classification accuracy.The FCLS-CA model has a higher accuracy and is able to identify most water bodies in the study area,and is therefore suitable for desert lake monitor-ing in mining areas.

CeTrivium:A Stream Cipher Based on Cellular Automata for Securing Real-Time Multimedia Transmission

Due to their significant correlation and redundancy,conventional block cipher cryptosystems are not efficient in encryptingmultimedia data.Streamciphers based onCellularAutomata(CA)can provide amore effective solution.The CA have recently gained recognition as a robust cryptographic primitive,being used as pseudorandom number generators in hash functions,block ciphers and stream ciphers.CA have the ability to perform parallel transformations,resulting in high throughput performance.Additionally,they exhibit a natural tendency to resist fault attacks.Few stream cipher schemes based on CA have been proposed in the literature.Though,their encryption/decryption throughput is relatively low,which makes them unsuitable formultimedia communication.Trivium and Grain are efficient stream ciphers that were selected as finalists in the eSTREAM project,but they have proven to be vulnerable to differential fault attacks.This work introduces a novel and scalable stream cipher named CeTrivium,whose design is based on CA.CeTrivium is a 5-neighborhood CA-based streamcipher inspired by the designs of Trivium and Grain.It is constructed using three building blocks:the Trivium(Tr)block,the Nonlinear-CA(NCA)block,and the Nonlinear Mixing(NM)block.The NCA block is a 64-bit nonlinear hybrid 5-neighborhood CA,while the Tr block has the same structure as the Trivium stream cipher.The NM block is a nonlinear,balanced,and reversible Boolean function that mixes the outputs of the Tr and NCA blocks to produce a keystream.Cryptanalysis of CeTrivium has indicated that it can resist various attacks,including correlation,algebraic,fault,cube,Meier and Staffelbach,and side channel attacks.Moreover,the scheme is evaluated using histogramand spectrogramanalysis,aswell as several differentmeasurements,including the correlation coefficient,number of samples change rate,signal-to-noise ratio,entropy,and peak signal-to-noise ratio.The performance of CeTrivium is evaluated and compared with other state-of-the-art techniques.CeTrivium outperforms them in terms of encryption throughput while maintaining high security.CeTrivium has high encryption and decryption speeds,is scalable,and resists various attacks,making it suitable for multimedia communication.

Modeling urban land use dynamics using Markov-chain and cellular automata in Gondar City,Northwest Ethiopia

Modeling urban land-use dynamics is critical for urban experts’and infrastructure managers’planning.This study attempts to explore the land-use/land-cover(LULC)dynamics of Gondar using satellite images from 1984 to 2020.Markov-Chain and Cellular Automata(MC-CA)models have been recognized as performing well in predicting urban land-use change.However,only a few models work in Ethiopia in general,and no study in Gondar has applied this approach to study urban land-use patterns.Therefore,Gondar land-use/land cover changes of Gondar were predicted using the MC-CA model in IDRISI.The built-up area in Gondar city covered 1413 ha(3%of the total area)in 1984 and increased to 2380 ha(5%)in 1994;21153 ha(45.5%)in 2004;22622 ha(48.7%)in 2014;and 23427 ha(50.5%)in 2020.The area has been predicted to reach 57.5%in the 2050s,showing a faster increase that will cause a very vast loss of farmland.This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade.Thus,innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

Analytical method for cell displacement defect quantum-dot cellular automata primitive

Quantum-dot cellular automata(QCA)is an emerging computational paradigm which can overcome scaling limitations of the existing complementary metal oxide semiconductor(CMOS)technology.The existence of defects cannot be ignored,considering the fabrication of QCA devices at the molecular level where it could alter the functionality.Therefore,defects in QCA devices need to be analyzed.So far,the simulation-based displacement defect analysis has been presented in the literature,which results in an increased demand in the corresponding mathematical model.In this paper,the displacement defect analysis of the QCA main primitive,majority voter(MV),is presented and carried out both in simulation and mathematics,where the kink energy based mathematical model is applied.The results demonstrate that this model is valid for the displacement defect in QCA MV.

One Hot Encoding Synthesis of Quantum Automata from Flowcharts

We present a new approach to the synthesis of quantum automata. In previous research, reversible quantum automata were designed from tabular specifications or state graphs, and minimum length codes, which lead to circuits with Toffoli gates with high numbers of inputs and thus to high quantum costs. This paper is the first to present a method to synthesize Sequential Quantum Circuits directly from flowcharts. In this paper, we directly map flowcharts to reversible/quantum circuits, using only inverters, 2*2 Feynman gates and 3*3 Toffoli gates, and thus reducing quantum costs. Our method has been confirmed by experiments on several benchmarks of practical flowcharts.

N×N Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata(QCA)

Quantum dot cellular automata(QCA)technology is emerging as a future technology which designs the digital circuits at quantum levels.The tech-nology has gained popularity in terms of designing digital circuits,which occupy very less area and less power dissipation in comparison to the present comple-mentary metal oxide semiconductor(CMOS)technology.For designing the rou-ters at quantum levels with non-blocking capabilities various multi-stage networks have been proposed.This manuscript presents the design of the N×NClos switch matrix as a multistage interconnecting network using quantum-dot cellular automata technology.The design of the Clos switch matrix presented in the article uses three input majority gates(MG).To design the 4×4 Clos switch matrix,a basic 2×2 switch architecture has been proposed as a basic mod-ule.The 2×2 switching matrix(SM)design presented in the manuscript utilizes three input majority gates.Also,the 2×2 SM has been proposed usingfive input majority gates.Two different approaches(1&2)have been presented for designing 2×2 SM usingfive input majority gates.The 2×2 SM design based on three input majority gate utilizes four zone clocking scheme to allow signal transmis-sion.Although,the clocking scheme used in 2×2 SM using three input MG and in 2×2 SM approach 1 usingfive input MG is conventional.The 2×2 SM approach 2 design,utilizes the clocking scheme in which clocks can be applied by electricfield generators easily and in turn the switch element becomes physically realizable.The simulation results conclude that the 2×2 SM is suitable for designing a 4×4 Clos network.A higher order of input-output switching matrix,supporting more number of users can utilize the proposed designs.

面向虚拟连挂的城轨列车群组追踪运行仿真研究

城市轨道交通是解决城市交通拥堵问题最强有效的绿色交通方式,其高峰期客流激增且客流时空分布不均,而面向虚拟连挂的城轨列车动态灵活编组和群组追踪运行能有效满足复杂多变的城轨运营需求。本文剖析面向虚拟连挂的城轨列车群组追踪运行过程,给出虚拟连挂列车群组最小安全追踪距离计算公式;以单列标准车长的线路路段为一个元胞单元,设计速度及位移更新规则,构建基于元胞自动机的城轨列车群组追踪运行仿真模型;以某市地铁2号线为背景,多角度仿真刻画面向虚拟连挂的城轨列车群组追踪运行性能。仿真结果表明:面向虚拟连挂的城轨列车群组追踪运行模型能有效缩短列车最小安全追踪间隔时间,城轨线路通过能力较移动闭塞制式提高78.4%;头车延迟引起的后续列车晚点总数量及总晚点时间更小,呈现出更佳的抗干扰性与恢复性能,且宜采用小编组列车实现虚拟连挂;动态混合编组的城轨列车群组追踪运行性能最佳,单一小编组的次之,大编组列车群宜在小编组列车群前面运行;城轨列车群组旅行速度总体上与平均站间距呈正相关;当列车发车间隔大于延迟时间时,平均站间距对列车群组的延迟影响不敏感,相反,则影响较为显著。研究结论能够为面向虚拟连挂的城轨列车群组追踪运行决策提供技术支撑。

考虑恐慌行人和多救援人员分区引导的疏散研究

为了探究紧急情况下多救援人员对恐慌行人疏散的影响,建立了一个考虑恐慌行人和多救援人员分区引导的元胞自动机扩展模型。首先,在模型中引入了恐慌因子Pm(t)定量反应恐慌情绪对行人疏散的影响;然后,考虑当多个救援人员存在时,协作开展分区救援的行为;最后,通过仿真重点分析了恐慌情绪阈值、救援人员数量及危险源位置对疏散动力学的影响。结果表明:恐慌情绪阈值和危险源位置显著影响人群的恐慌传播过程和疏散过程;救援人员的引导提高了疏散效率;当多名救援人员存在时,实行分区引导更有利于疏散;出现救援人数不足时,根据危险源的位置和恐慌传播过程对疏散的影响合理地分配救援人员能够提高疏散效率。

点蚀效应下超强钢丝疲劳损伤演化及寿命预测

主缆作为悬索桥不可更换的关键承重构件,其钢丝的疲劳寿命将直接影响桥梁的安全性和耐久性。由于主缆通常暴露于侵蚀环境中,往往会产生不同形式的腐蚀效应,其中点蚀是一种破坏力强且十分典型的腐蚀损伤,通常会成为疲劳裂纹萌生的初始点,从而显著降低构件的疲劳寿命。为研究点蚀效应对超高强钢丝疲劳性能的影响,采用能反映腐蚀电化学机理的元胞自动机模型模拟点蚀复杂形成过程,并基于盐雾试验标定演化参数,获得超高强钢丝的表面点蚀坑模型;在ABAQUS中开发基于连续损伤力学的UMAT子程序,实现腐蚀钢丝的疲劳损伤演化与寿命预测,揭示腐蚀程度、蚀坑形状参数对超高强钢丝的损伤演化规律和疲劳寿命的影响。结果表明:采用元胞自动机方法能够准确模拟钢丝点蚀过程,生成的模型可以很好地展现真实的蚀坑形态和特征;在蚀坑处最早出现损伤,前中期损伤速率较慢,后期发展迅速;随着疲劳荷载的加载,蚀坑处会发生应力重分布现象,蚀坑底部的应力逐渐降低,周边应力反而增加;在元胞自动机中以质量损失率表征钢丝腐蚀程度,当钢丝的质量损失率从0.1%增加到0.25%时,其疲劳寿命减少约36.8%;点蚀坑的深宽比越大,形状越尖锐,钢丝越容易发生疲劳破坏。研究结果可为腐蚀环境下超高强钢丝的疲劳寿命评估和提高桥梁的耐久性提供参考。

基于角色的区块链拍卖合约抽象建模及其时间安全性与公平性验证

为提升拍卖合约时间安全性验证效率及验证公平性,提出基于角色的拍卖合约抽象建模及其验证方法。首先,对合约源代码进行基于账户角色的抽象建模,转换为时间自动机网络模型,并对时间安全性进行形式化描述,用UPPAAL工具验证。其次,提取合约源代码机制,建立智能合约机制模型,同样转换为时间自动机网络模型,并对4种公平性进行形式化描述,再用UPPAAL验证。最后,通过2个经典案例证明了所提方法的可行性和有效性。

基于元胞自动机的高速公路主线同侧连续入口间距研究

针对高速公路主线同侧连续入口处车辆行驶安全与通行效率问题,对高速公路主线同侧连续入口间距进行了研究。通过建立元胞自动机仿真模型,分析了主线与匝道设计速度的差异以及高速公路主线匝道连续入口间距各部分长度对交通冲突率、平均拥堵车辆数和平均速度的影响;提出了不同主线与匝道设计速度组合下的主线同侧连续匝道入口间距推荐值;并对不同间距组合下的工况进行了仿真对比分析。研究结果表明:当主线与匝道设计速度的差异较大时,现有规范中的高速公路主线同侧连续入口间距难以满足交通安全与通行效率要求;相比采用规范中的一般值,采用文中推荐值时的主线车辆平均速度由81.39 km/h上升到95.29 km/h,匝道车辆冲突率由0.0335次/(km·veh)下降到0.0256次/(km·veh),匝道车辆平均拥堵数由0.0077 veh/s下降到0.0022 veh/s,提高了车辆通行效率,降低了车辆发生事故的风险。

结构拓扑优化的Q学习-元胞方法研究

传统的拓扑优化算法均基于灵敏度分析的方式求解,如渐进结构优化法(Evolutionary Structural Optimization, ESO)和变密度法(Solid Isotropic Material with Penalization, SIMP)等,灵敏度分析依赖于严谨的数学模型,结果可信度高,但面对不同的结构和约束条件都需要反复重新推导单元灵敏度,对使用人员的数学能力有较高要求,而且也导致了收敛速度慢、迭代步数多的问题。针对现有优化方法中存在的缺陷,结合强化学习Q学习理论和元胞自动机原理,提出一种新的拓扑优化方法:Q学习-元胞法(Q-learning-Cellular Automaton, QCA),尝试为工程构件的优化设计提供一种新思路。这种方法以有限元单元作为元胞,将所有元胞的智能行为集成为一个Q-learning智能体。训练过程中,各个元胞首先完成对自身环境的感知,然后调用智能体进行决策并通过环境交互得到反馈,智能体也借此得到大量数据来学习更新,整个过程不涉及数学模型推导,通过智能体和元胞的不断探索即可完成优化。在此基础上,探讨元胞的选择及其邻域和状态的描述方式,针对元胞的动作空间及收益函数进行比选,进而编制相关拓扑优化软件。优化算例表明,QCA方法优化后的拓扑构型与传统优化方法的构型基本一致,迭代步数较SIMP法降低了64%,且柔顺度更低。Q学习-元胞法在结构拓扑优化中具备良好的可行性,计算效率高且具有迁移优化能力,在结构拓扑优化领域极具潜力。

基于扰动时空混沌的三维OFDM星座加密方案

无线通信网络的迅猛发展使得传输信息量迅速增加,这对系统的传输效率和通信安全提出了更高的要求。为满足上述要求,提出了一种基于扰动时空混沌的三维OFDM星座加密方案。首先,设计了一种反馈元胞自动机,以提高元胞自动机的周期性和伪随机性。将反馈元细胞自动机的迭代结果进行归一化后,作为扰动加入时空混沌系统中。通过分岔图、李亚普诺夫指数、回归映射分析和随机性测试,证明了添加该扰动的系统具有良好的混沌特性。其次,设计了一种新的三维16-ary星座图,将星座点之间的最小欧氏距离扩大了6.3%,并结合扰动的时空混沌系统实现了三维星座旋转的物理层调制加密。实验仿真结果表明,与其他三维16-ary星座映射旋转加密算法相比,该算法的误码率性能提高了约1 dB。此外,通过密钥空间、密钥灵敏度和统计攻击的安全分析,证明了其良好的安全性能。

考虑恐慌情绪和信息传递的行人疏散模拟

为分析应急疏散过程中恐慌情绪和信息传递对行人疏散效率的影响,提出基于热传递原理的情绪感染模型和元胞自动机场域模型相结合的疏散模拟方法。该方法通过量化的恐慌值影响行人决策偏好,并引入信息扩散模型,修正成功接收到出口信息的人群的疏散路径,模拟研究恐慌情绪作用下行人受到信息引导后疏散行为的变化。研究结果表明:恐慌情绪感染主要出现在人群聚集时期,伴随恐慌的蔓延,整体疏散效率降低,且对小规模行人疏散影响效果更显著;随着危险源向出口靠近,恐慌情绪使行人做出非理性决策的可能性更大,导致出口处人群出现分散再聚集现象;有效的信息传递可以降低恐慌情绪影响、提高疏散出口利用率,且信息传递影响效果随疏散人数的减少和危险源向出口的靠近而有所增强。研究结果可为提升应急疏散效率提供理论支持。

基于多层元胞自动机的动态随机耦合映像格系统性能分析

基于多层元胞自动机的时空混沌系统设计了一款用于图像加密的伪随机数发生器.针对现有的基于耦合映像格系统仍存在参数空间有限、局部混沌行为等问题,本文提出一种基于多层元胞自动机的伪随机耦合映像格系统.在初等元胞自动机基础上设计出多层元胞自动机,将耦合系统与多层元胞自动机同时进行迭代,通过自动机的迭代输出得到耦合系统中每个格子的动态耦合方案以及伪随机扰动方法.本文通过分岔图、Kolmogorov Sinai熵和输出序列均匀性对耦合映像格系统进行对比分析,并分析了系统生成序列的随机性和任意两个格之间的相关性.理论分析和实验结果表明,与其它耦合映射格系统相比,该系统具有更好的混沌特性和更大的参数空间,系统生成的序列具有较好的遍历性、均匀性和随机性.研究结果表明该系统在密码学领域具有广阔的应用前景.

车联网环境下车辆上匝道元胞自动机仿真模拟

为了验证车联网下的交通效率与安全水平,针对高水平车联网下的车辆上匝道过程进行了元胞自动机仿真。针对主道为双车道的上匝道场景,在换道规则上提出了协同换道规则,改进了强制换道规则,从而建立了考虑安全距离和互联性的元胞自动机模型。并模拟了智能网联车与普通人工车混合排列下的交通效率与安全状况。当车流密度较大时,不同车辆排列方式的指标值差异显著。在交通效率方面,当智能网联车渗透率高时,出流量较大且平均速度在20m/s处聚集。说明智能网联车对交通效率有积极影响,而普通人工车的长队列对交通效率有消极作用。在交通安全方面,碰撞时间与临界指数函数值的分布结果均表明,混行情况下智能网联车形成的长队列有利于交通安全,而普通人工车的聚集对交通安全不利。

考虑折返行为的元胞自动机人员疏散模型

为研究行人折返行为对疏散的影响,考虑多出口对行人的吸引力、人员相互作用力、火源蔓延威胁以及折返场吸引力的共同影响,在元胞自动机模型的基础上提出基于静态场、动态场、火源场以及折返场共同作用的行人疏散场域模型,研究不同折返比例、折返区域、人员密度、出口数量和位置情况下折返行为对疏散进程的影响。研究结果表明:少量折返行为对总疏散时间影响较小,而群体性折返行为的存在会增加总体疏散时间,随着折返比例的增加,疏散时间随之增加。折返区域离出口越近,对总体疏散效率的影响越小。折返行为对疏散进程的影响效果,随着人员密度的增加不断增强。在双出口条件下,对侧设置出口位置能有效减少折返行为对疏散进程的负面影响。研究结果可为提高紧急情况下的疏散效率提供参考。

基于CA-RL的堆石坝填筑仓面碾压作业动态路径规划

碾压作业是堆石坝填筑仓面施工的关键工序,科学合理规划碾压路径能够在保障碾压质量的前提下提高碾压效率。在当前路径规划研究基础上进一步考虑碾压机数量变化、压实质量感知等动态要素可以提高路径规划模型面对复杂动态的仓面施工环境的适应性。本文通过建立基于元胞自动机的填筑仓面信息模型、提出条带整体压实质量评价方法,解决压实质量等仓面信息的储存更新的问题;通过建立基于强化学习的碾压作业路径规划模型、构建碾压机状态集和动作集、设计奖励函数和探索利用策略,解决碾压机数量变化的路径分配的问题;耦合上述两种模型,实现堆石坝填筑仓面碾压作业动态路径规划。结合国内某堆石坝工程开展了工程应用,结果表明:本方法可动态考虑碾压机数量变化、压实质量感知等要素,路径规划结果在保障碾压质量的前提下路径长度相较现场施工实际路径平均缩短22.3%,能够有效提升碾压效率。