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.

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.

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.

Modeling of rock failure based on physical cellular automata

To analyze the effects of heterogeneous material characteristics on rock failure,a micro-heterogeneous physical cellular automata （Mh-PCA） model is introduced according to the cellular automata theory from a general power view.In this model,the neighbor is the Moore pattern and the Weibull distribution is adopted to simulate the rock heterogeneousness.Using this model,the evolvements and acoustic emission of rock failure are simulated for four materials of different degree of homogeneousness （m＝1,5,10,15）.The results show that the heterogeneous characteristic has a great effect on the rock failure,the more the homogeneousness,the fewer the crack branches and the more concentrated acoustic emissions.The physical cellular automata theory gives a new idea for studying rock failure.

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。

Three-dimensional cellular automata based particle flow simulations of mechanical properties of talus deposit

Based on three-dimensional cellular automata （CA）, a new stochastic simulation model to simulate the microstructures and particle flow of talus deposit is proposed. Ill addition, an auto-modeling program CARS is developed, with which nunaerical simulations can be conducted conveniently. For the problem of simulating mechanical behaviors of talus deposit, spatial anangement or sphere shapes should be considered. In the new modeling method, four sphere anangement models are developed for the particle flow simulation of talus deposit. Numerical results show that the talus deposit has the mechanical characteristics of typical stress-strain curves, as other rock-like materials. The cohesion of talus deposit decreases with increasing rock content, while the internal friction angle increases with increasing rock contents. Finally, numerical simulation is verified with the results of field test.

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 investigation of the boundary-triggered phase transition dynamics in a cellular automata model with a slow-to-start rule

Previous studies suggest that there are three different jam phases in the cellular automata automaton model with a slow-to-start rule under open boundaries.In the present paper,the dynamics of each free-flow-jam phase transition is studied.By analysing the microscopic behaviour of the traffic flow,we obtain analytical results on the phase transition dynamics.Our results can describe the detailed time evolution of the system during phase transition,while they provide good approximation for the numerical simulation data.These findings can perfectly explain the microscopic mechanism and details of the boundary-triggered phase transition dynamics.

精细刻画城镇自组织扩展过程的CA-ABM耦合模拟及预测模型

城镇扩展模拟预测是支撑国土空间规划、实现城镇化高质量发展的重要手段,提高其科学性和实用性有助于精确把握城镇扩展趋势,对国土资源的合理和可持续利用意义重大。现有以元胞自动机(CA)为基础的模型着重于刻画空间因子驱动的城镇自然扩展过程,智能体模型(ABM)则在模拟城镇自组织扩展方面具有理论优势,而且已有的耦合方法多为基于模拟步骤的模型级联,难以实现二者紧密耦合以充分发挥其在模拟城镇自然和自组织扩展方面的优势。本文基于CA的结构开放性和ABM的理论优势,以可达性为媒介表征城镇扩展局部自组织过程的范围差异,并依据博弈论设计利益相关者之间的局部自组织规则,将ABM刻画的人地交互决策融入CA邻域构建,建立一种可以精细刻画城镇自组织扩展过程的CA-ABM耦合模拟及预测模型(CA-ABM-LSO),实现CA和ABM在底层结构的深度集成和城镇自然与自组织扩展过程的耦合模拟。以武汉市为例对其进行应用,结果表明:基于CA和ABM的优势互补特点进行耦合建模,能够充分发挥二者在刻画城镇自然和自组织扩展方面的优势,显著提升城镇扩展模拟精度,并改善模拟城镇斑块的景观形态;基于博弈论的局部自组织规则可有效实现宏观经济政策对微观智能体交互决策的指导,提高城镇扩展模拟的科学性和规划实用性;预计至2035年,武汉市城镇扩展的重点区域集中在高新科技园区和运输集散中心附近,这符合“武鄂黄黄”都市圈的发展预期,可为其空间规划提供决策支持。

基于ANN-CA的外来入侵植物互花米草的扩散趋势预测研究

采用遥感技术手段对九段沙互花米草(Spartina alterniflora)信息提取与动态监测基础上,开展滨海地区互花米草入侵时空特征分析、入侵地区景观演变规律以及预测互花米草扩散趋势等研究对于沿海城市生态环境协调发展具有重要的意义。选取邻域因子、生态属性和地理属性等相关变量因子,耦合人工神经网络(ANN)与元胞自动机(CA),基于2015-2019年间九段沙互花米草与其他湿地景观类型数据构建ANN-CA模型,采用3层BP神经网络,在不断训练与校正与验证模型精度的基础上,对2019年九段沙区域互花米草进行模拟,采用Lee-Sallee形状指数来对比模拟分类结果与实际分类结果在空间分布层面的相似度,并进行相应的模型校正,在此基础上预测2025年九段沙互花米草扩散与群落分布格局,为互花米草的扩张趋势、景观演变以及分布扩散预测提供理论依据和科学基础。结果表明,1)1995-2025年间互花米草自从引种定居到不断扩张,所呈现的面积变化图近乎S型曲线,其中2015-2019年面积增长了847 hm^(2),2019-2025年面积增长了646 hm^(2),因此互花米草在九段沙自然保护区的动态扩散,分别为定居阶段、滞缓阶段、快速增长阶段以及缓慢增长阶段。2)2025年九段沙区域互花米草的扩张速率从趋势看已进入扩张的缓慢期,与前几年相比尽管有所增加,但趋势有所放缓。3)构建的ANN-CA模型能够较好地对九段沙自然保护区的植被演变进行模拟和预测。

Performance Evaluation of Efficient XOR Structures in Quantum-Dot Cellular Automata (QCA)

Quantum-dot cellular automaton (QCA) is an emerging, promising, future generation nanoelectronic computational architecture that encodes binary information as electronic charge configuration of a cell. It is a digital logic architecture that uses single electrons in arrays of quantum dots to perform binary operations. Fundamental unit in building of QCA circuits is a QCA cell. A QCA cell is an elementary building block which can be used to build basic gates and logic devices in QCA architectures. This paper evaluates the performance of various implementations of QCA based XOR gates and proposes various novel layouts with better performance parameters. We presented the various QCA circuit design methodology for XOR gate. These layouts show less number of crossovers and lesser cell count as compared to the conventional layouts already present in the literature. These design topologies have special functions in communication based circuit applications. They are particularly useful in phase detectors in digital circuits, arithmetic operations and error detection & correction circuits. The comparison of various circuit designs is also given. The proposed designs can be effectively used to realize more complex circuits. The simulations in the present work have been carried out using QCADesigner tool.

Desertification evolution prediction for lake area of Minqin oasis based on integration of GIS and cellular automata

The Minqin oasis is surrounded on three sides by the Tengger Desert and the Badanjilin Desert, and it prevents these two deserts from converging. However, in recent years it has become the worst ecological environment in the Lake area due to deficient water resources, continual declines in the groundwater level and quality （increasing mineralization and salination）, which are causing in- creasing desertification. In this study, Landsat Thematic Mapper （TM） remote images from 1992, 1998, 2002, and 2006 of the Lake area of the Minqin oasis are interpreted to analyze the desertification evolution. A combination of an ArcObjects module and a cellular automata model is used to build a model simulating the desertification dynamics; the forecasting accuracy of this model is shown to reach up to 90%. The desertification situation in 2012 is forecasted by this model, and the results showed that, from 2006 to 2012, the green land area will be reduced by 999.92 hm2 （l.59 percent of the total oasis area）, the desertification land area will be reduced by 3,000.68 hrn2 （4.78 percent of the total oasis area）, and sand land area will increase by 4,000.6 hm2 （6.37 per- cent of the total oasis area）. The sand land is predicted to become more widespread, and more than 18% sand land will be distrib- uted in the center of green land in the Lake area. In other words, more and more abandoned green land （mined farm land） will be transformed into sand land, and this will intensify the desertification.

TOPOLOGICAL ENTROPY OF PERIODIC COVEN CELLULAR AUTOMATA

We investigate topological entropy of periodic Coven cellular automatas; that is, the maps Fs： （0, 1）^z → {0, 1）^z defined by FB（x）i=xi＋^rПj=1（xi＋j＋bj）（mod 2）, where B = b1b2…br ∈ {0, 1}^r（r≥2）, is a periodic word. In particular, we prove that if the minimal period of B is greater than 5, the topological entropy is log 2.

Forecast of Dynamic Change of Land Use Based on Cellular Automata

Land use change is a very complex process of evolution.On the basis of the principle of cellular automata,this article presents a kind of method that we can first mine state transition rule from historical map data,and then conduct forecast by virtue of Monte-Carlo method,achieving spatial dynamic forecast from map to map.We interpret TM remote sensing image in Ji'nan City in 2004 and 2006 to get present land use map for empirical research,and forecast land use map in 2012 and 2016,respectively.Studies show that this method of using spatial data to mine state transition rule,has advantages of simpleness,accuracy,strong real-time characteristic etc.in the simulation of dynamic change of land use,the results of which are roughly in line with the actual results,therefore,it can provide reference for land use planning.

Modeling Agricultural Change through Logistic Regression and Cellular Automata: A Case Study on Shifting Cultivation

Agricultural expansion is one of the prime driving forces of global land cover change. Despite the increasing attention to the factors that cause it, the patterns and processes associated with indigenous cultivation systems are not well understood. This study analyzes agricultural change associated with subsistence-based indigenous production systems in the lower Pastaza River Basin in the Ecuadorian Amazon through a spatially explicit dynamic model. The model integrates multiple logistic regression and cellular automata to simulate agricultural expansion at a resolution consistent with small scale agriculture and deal with inherently spatial processes. Data on land use and cultivation practices were collected through remote sensing and field visits, and processed within a geographic information system framework. Results show that the probability of an area of becoming agriculture increases with population pressure, in the vicinity of existing cultivation plots, and proximity to the center of human settlements. The positive association between proximity to cultivation areas and the probability of the presence of agriculture clearly shows the spillover effect and spatial inertia carried by shifting cultivation practices. The model depicts an ideal shifting cultivation system, with a complete cropping-fallow-cropping cycle that shows how agricultural areas expand and contract across space and over time. The model produced relatively accurate spatial outputs, as shown by the results of a spatial comparison between the simulated landscapes and the actual one. The study helped understand local landscape dynamics associated with shifting cultivation systems and their implications for land management.

Comparison of Urban Growth Modeling Using Deep Belief and Neural Network Based Cellular Automata Model—A Case Study of Chennai Metropolitan Area, Tamil Nadu, India

Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to predict the urban growth more close to reality. Recently, deep learning based techniques are being used for the prediction of urban growth. In this current study, urban growth of Chennai Metropolitan Area (CMA) of 2017 was predicted using Neural Network based Cellular Automata (NN-CA) model and Deep belief based Cellular Automata (DB-CA) model using 2010 and 2013 urban maps. Since the study area experienced congested type of urban growth, “Existing Built-Up” of 2013 alone was used as the agent of urbanization to predict urban growth in 2017. Upon validating, DB-CA model proved to be the better model, as it predicted 524.14 km2 of the study area as urban with higher accuracy (kappa co-efficient: 0.73) when compared to NN-CA model which predicted only 502.42 km2 as urban (kappa co-efficient: 0.71), while the observed urban cover of CMA in 2017 was 572.11 km2. This study also aimed at analyzing the effects of different types of neighbourhood configurations (Rectangular: 3 × 3, 5 × 5, 7 × 7 and Circular: 3 × 3) on the prediction output based on DB-CA model. To understand the direction and type of the urban growth, the study area was divided into five distance based zones with the State Secretariat as the center and entropy values were calculated for the zones. Results reveal that Chennai Corporation and its periphery experience congested urbanization whereas areas away from the Corporation boundary follow dispersed type of urban growth in 2017.

Single-Bit Comparator in Quantum-Dot Cellular Automata (QCA) Technology Using Novel QCAXNOR Gates

To fill the continuous needs for faster processing elements with less power consumption causes large pressure on the complementary metal oxide semiconductor(CMOS)technology developers.The scaling scenario is not an option nowadays and other technologies need to be investigated.The quantum-dot cellular automata(QCA)technology is one of the important emerging nanotechnologies that have attracted much researchers’attention in recent years.This technology has many interesting features,such as high speed,low power consumption,and small size.These features make it an appropriate alternative to the CMOS technique.This paper suggests three novel structures of XNOR gates in the QCA technology.The presented structures do not follow the conventional approaches to the logic gates design but depend on the inherent capabilities of the new technology.The proposed structures are used as the main building blocks for a single-bit comparator.The resulted circuits are simulated for the verification purpose and then compared with existing counterparts in the literature.The comparison results are encouraging to append the proposed structures to the library of QCA gates.