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.

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。

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。

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。

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。

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。

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。

高速公路混合交通环境下的智能网联汽车换道策略研究

为推动智能网联汽车应用落地,提出高速公路混合交通环境下智能网联汽车换道策略。首先,改进NaSch元胞自动机模型,并采用马尔科夫链算法计算道路通行能力;其次,针对目标车道为专用车道和普通车道分别建立基于车速引导的决策模型和基于博弈论的双矩阵决策模型;最后,采用多目标轨迹优化算法优化换道轨迹。结果表明:目标车道为专用车道和普通车道时,所提出的策略可分别提高换道效率6%、3.38%。

船舶超大空间火灾环境下人员疏散模型

针对船舶超大空间火灾对人员疏散能力的影响难以量化问题,本文基于元胞自动机理论,构建了一种行人个体自主分析火灾环境下温度和能见度影响的疏散模型(cellular automata model considering visibility and temperature, CAVT)。CAVT模型采用Sigmoid函数和历史实验数据建立温度、能见度与人员运动能力的映射关系,基于FDS数值模拟结果建立火灾环境场对人员个体运动能力影响的时空耦合关系,使用熵值法计算温度场和能见度场在火灾环境场中的权重。以某客船超大空间为例开展研究分析,结果表明:火灾环境下人员疏散时间受火源功率影响较大,火源位置影响较小,出口宽度大于3 m,不影响疏散效率。与Pathfinder软件相比,CAVT模型可更准确模拟人员因高温和低能见度导致的运动能力的动态下降反馈。

基于时间自动机的动力调度岗位培训仿真机理建模

针对大型风洞群中压空气系统存在调度机理复杂、岗位人员素质要求高、系统实操培训代价大等问题,实施基于时间自动机的动力调度岗位培训仿真机理建模。通过混杂系统理论提出适合大型风洞群中压空气调度的扩展时间自动机模型,基于先来先服务策略构建资源申请、机组工作等队列,建立调度器、就地执行器等核心机理模型,并采用UPPAAL工具对模型进行验证。结果表明:该模型的建立不仅为岗位人员掌握设备结构原理、积累实操经验提供有效手段,而且为建立风洞试验调度仿真系统、合理有效实施风洞动力调度岗位培训打下了基础。

求解多维复杂函数及真实世界工程设计问题的高效海洋捕食者算法

针对海洋捕食者算法在面对复杂函数和工程设计优化问题时存在的自适应能力有限、寻优精度有时较低、局部桎梏概率较高等缺点,提出一种新的高效自适应海洋捕食者算法.首先在海洋记忆存储阶段引入学习自动机引导的教与学搜索机制,更好地平衡算法在不同迭代时期对探索和挖掘能力的不同需求;然后在局部开发阶段,引入对数螺旋探索机制,加强算法在最优解附近的精细挖掘能力,进一步提高收敛精度;最后在算法中每次迭代末尾处加入改进的自适应相对反射策略,提升种群跳出局部最优的能力,降低局部桎梏概率.为了分析和验证该改进算法的性能,将其和6种代表性算法在进化计算大会(CEC)2017测试套件上进行100维的函数极值测试,并在4个具有挑战性的工程设计优化问题上进行测试.测试结果表明在求解多维复杂函数和工程设计优化问题时,本文改进算法的寻优精度、收敛性能和求解稳定性明显优于其他6种代表性算法,尤其在高维复杂函数下,其寻优性能的优越性更为显著.

基于遗传算法的元胞自动机复杂楼宇人员疏散模型

为探究复杂楼宇人员疏散的效果,该文基于元胞自动机理论,建立了复杂楼宇人员疏散模型。选取某高校实验中心为应用场景,综合考虑了疏散路径、出口安排、人群密度和人员行为等多种因素,分析引导选择出口、引导使用连廊和基于遗传算法的适应度函数三种优化方式对疏散效果的影响,并将此模型计算结果与模拟软件Pathfinder计算结果进行对比验证。结果表明,随着优化程度的提高,疏散总时间和极度拥堵面积减少,有效地降低了高人群密度区域,提高了出口使用均衡性,疏散效果得到了显著提升。