基于SD-CA-GIS的环境累积效应时空分析模型及应用

环境累积效应分析强调环境变化的时空放大作用,突出环境要素之间的时空交互作用,从而对环境分析方法的能力提出了挑战.因此,本文在对传统环境分析方法归纳、分析和总结的基础上,以地理信息系统(GIS)为基础平台,集成系统动力学(SD)和元胞自动机(CA)的优点,建立了能够分析时间累积、空间累积效应的SD-CA-GIS模型.以山西潞安矿区作为研究区域,在分析矿区社会、经济、工程和环境等因子之间时空交互作用的基础上,构建了SD-CA-GlS模型.考虑到矿区土地利用变化的特殊性,从影响矿区土地利用变化的驱动因子出发,预测和模拟了矿区2006-2030年土地利用变化的累积状况.结果发现,由于煤炭资源开采等人类干扰活动的影响,研究区在研究时段内,工矿用地、居民用地和交通用地呈现累积性增加,其它土地利用类型累积性减少.同时,由于不同阶段人类活动干扰的种类和强度变化,使得不同土地利用类型的空间扩展变化存在一定的差异.上述研究表明,该模型能够同时考虑时间累积效应和空间累积效应的动态变化,能为环境累积效应的分析和评价提供有效的帮助.     

细胞自动机模拟活性污泥法污水处理过程

从活性污泥法污水处理过程的微观机理出发,建立了污水处理过程的二维细胞自动机模型,并进行仿真实验.结果表明：建立的细胞自动机模型能够实现污水处理过程的动态可视化,复现出了污水中有机物被吸附、降解及微生物生长、繁殖和衰亡的过程;仿真中还讨论了污泥颗粒粒径、有机物分子半径、温度和污泥浓度等因素对模拟结果的影响,因素灵敏度分析...     

基于CA的城市形态扩展多解模拟——以北京市东部平原区情景分析为例

构建了一个基于人工神经网络的约束型城市扩展CA模型。利用该模型,预测了北京市东部平原区在3种情景规划之下的未来50年的城市形态,为不同的城市发展模式之间的比较分析奠定基础。然后以2024年的北京东部平原区模拟城市形态为基准,从自然生态功效、社会服务功效、经济利益功效3个方面对3种规划模式进行了情景分析,从而系统的比较了3种规划模式的复合生态功效,为城市规划决策提供有力的支持。     

基于CA-MAS的水域总有机碳扩散模拟研究

当前水环境污染扩散研究一般基于普通数值模型模拟,忽略了水污染扩散微观驱动力的影响。为能更真实地反映其动态扩散过程,针对水域总有机碳(TOC)扩散机理,基于CA和MAS技术,将影响TOC扩散的自然和社会经济因素抽象为微观的水流Agent、风速Agent、径流量Agent、污水排放口Agent、人工管理Agent以及农业生产地Agent,将研究水域抽象为CA元胞空间,建立了CA-MAS水域总有机碳扩散模型,对水域总有机碳的动态演化过程进行模拟,并以武汉理工大学鉴湖水域作为实验区域,借助NetLogo仿真平台完成了模型的实现与验证。模拟结果表明,该模型基本能够反映水体总有机碳的扩散规律,可以为水环境污染控制提供参考。     

Radiofrequency exposure in the French general population: Band, time, location and activity variability

Information on the exposure of individual persons to radiofrequency (RF) fields is scarce, although such data are crucial in order to develop a suitable exposure assessment method, and frame the hypothesis and design of future epidemiological studies. The main goal of this survey is to assess individual RF exposure on a population basis, while clarifying the relative contribution of different sources to the total exposure. A total of 377 randomly selected people were analyzed. Each participant was supplied with a personal exposure meter for 24-hour measurements (weekday), and kept a time–location–activity diary. Electric field strengths were recorded in 12 different RF bands every 13 s. Summary statistics were calculated with the robust regression on order statistics method. Most of the time, recorded field strengths were not detectable with the exposure meter. Total field, cordless phones, WiFi-microwave, and FM transmitters stood apart with a proportion above the detection threshold of 46.6%, 17.2%, 14.1%, and 11.0%, respectively. The total field mean value was 0.201 V/m, higher in urban areas, during daytime, among adults, and when moving. When focusing on specific channels, the highest mean exposure resulted from FM sources (0.044 V/m), followed by WiFi-microwaves (0.038 V/m), cordless phones (0.037 V/m), and mobile phones (UMTS: 0.036 V/m, UMTS: 0.037 V/m). Various factors, however, contributed to a high variability in RF exposure assessment. These population-based estimates should therefore be confirmed by further surveys to better characterize the exposure situation in different microenvironments.     

基于改进粒子群算法和元胞自动机的城市扩张模拟——以南京为例

为合理利用多智能体算法解决城市扩张动态模拟问题,基于地理学理论和社会学规律对粒子群算法进行有针对性的改进,提出分段式粒子群算法(SPSO),并结合元胞自动机模拟复杂时空过程的能力,构建出适用于城市扩张模拟的地理元胞自动机SPSO-CA。在SPSO-CA中我们利用多时像的土地利用数据、交通路网数据和地形数据,挖掘出1995~2000年南京城市扩张的土地转换规则。再由此规则实现1995~2008年的南京市城市扩张过程的动态模拟。最后对比SPSO-CA、PSOCA及NULL模型结果得:SPSO-CA总精度86.3%,Kappa系数为0.792,Moran’s I为0.078,PSO-CA总精度83.6%,Kappa系数为0.755,Moran’s I为0.054,NULL模型总精度81.9%,Kappa系数为0.741,真实的Moran’s I为0.072。这表明无论是总精度还是空间一致性,SPSO-CA都优于PSO-CA和NULL模型,即用SPSO-CA模拟城市扩张是可行的。     

大气污染排放窗口机制研究

以2种典型的污染排放源(点污染源和线污染源)为基础,提出排污窗口的概念,通过参数转换分解源强对污染扩散进行研究。首先在高斯污染扩散模型的基础上,对非持续性污染源强建模,然后以某烟囱的周期性排污分析,检验排污窗口设置的合理性。对于单双号限行的窗口性质的污染排放研究中,首先对交通流建立线污染扩散模型,然后融合元胞自动机(9元胞互影响)模拟区域多角度污染的扩散平衡,最后对"单双号限行"下北京市不同区域空气质量指标进行分析与仿真。分析结果表明,合理的排污窗口能够减轻污染程度及对人们日常生活的影响。     

元胞自动机在矿山地质灾害预测中的应用

本文根据复杂性科学理论,论证了地质灾害系统是一个复杂大系统。元胞自动机（Cellular Automata,CA）是一种重要的复杂性科学研究工具,本文阐述了元胞自动机的基本原理和方法,总结了其基本特点,认为元胞自动机在安全科学与技术领域有着广阔的应用前景,并探讨了其在滑波预测、地下水渗透、岩爆预测等几种矿山地质灾害预测中的应用。     

Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches

In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method; (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique; (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm.     

Evaluation of driver performance with a prototype cyber physical mid-block crossing advanced warning system

Introduction: Using connected vehicle technologies, pedestrian to vehicle (P2V) communication applications can be installed on smart devices allowing pedestrians to communicate with drivers by broadcasting discrete safety messages, received by drivers in-vehicle, as an alternative to expensive fixed-location physical safety infrastructure. Method: This study consists of designing, developing, and deploying an entirely cyber-physical P2V communication system within the cellular vehicle to everything (C-V2X) environment at a mid-block crosswalk to analyze drivers’ reactions to in-vehicle advanced warning messages, the impacts of the advanced warning messages on driver awareness, and drivers’ acceptance of this technology. Results: In testing human subjects with, and without, advanced warning messages upon approaching a mid-block crosswalk, driver reaction, acceptance, speed, eye tracking data, and demographic data were collected. Through an odds ratio comparison, it was found that drivers were at least 2.44 times more likely to stop for the pedestrian with the warning than without during the day, and at least 1.79 times more likely during the night. Furthermore, through binary logistic regression analysis, it was found that driver age, time of the day, and the presence of the advanced warning message all had strong, significant impacts with a confidence value of at least 98% (p < 0.02) on the rate at which drivers stopped for the pedestrian. Conclusions: The results from this study indicate that the advanced warning message sent within the C-V2X had a strong, positive impact on driver behavior and understanding of pedestrian intent. Practical Applications: Pedestrian crashes and fatality rates at mid-block crossings continue to increase over the years. Connected vehicle technology utilizing smart devices can be used as a means for communications between pedestrians and drivers to deliver safety messages. State and local city planners should consider geofencing designated mid-block crossings at which this technology operates to increase pedestrian safety and driver awareness.