时空大数据在空间优化中的应用

空间优化提供资源、实体等的高效配置与最佳空间组织方案,是地理学的重要研究领域。大数据背景下,各类蕴含时空信息的时空大数据能反映地表各要素的空间格局特征与演变过程,为空间优化提供强大的数据支撑。基于国内外时空大数据、空间优化研究成果,分析大数据发展历程、特征、定义及其影响,概括时空大数据的定义与特征,总结出对地观测、社会经济、物联网、互联网与社交网等5类时空大数据;在宏观(全国)、中观(省域)、微观(市县)3个尺度下,综述现有研究中的各种空间优化;将时空大数据在各类空间优化中的应用归纳为城市(镇)体系空间结构分析、自然生态环境监测、土地利用分析等7大类,并分别梳理了国内外的相关应用研究。该综述可为时空大数据、空间优化相关研究提供参考。     

载人潜水器圆柱形耐压壳体的优化设计研究

采用分枝定界法和序列二次规划方法,对载人潜水器圆柱形耐压壳体的重量最小化进行了研究.设计变量是壳板的厚度、肋骨的型号、间距和数量,讨论了下潜深度、材料几何参数对重量以及其它特征量的影响.算例计算表明,下潜深度越大,屈服极限越高的材料重量减轻越明显.对于大深度而言,选用高屈服极限材料,可以使得材料能够充分利用.文中还对结构重量占排水量比例随深度变化的情况进行了研究.     

雅安雨量站站网布设优化试验

雨量监测的准确性对天气预报、气候变化、服务决策、防灾减灾等有着重要的影响和意义,而雨量站网布设直接影响雨量监测的准确性。选取四川省雅安市作为研究对象,在现有站网布设的基础上,采用相关性分析,提出基于抽站的站网布设优化方法,并对抽站后的站网布设合理性进行评价。结果表明：(1)雅安雨量站有265站,各站点的控制面积为2.64～510.78 km²,邻近站间距离为0.3～12.28 km,邻近站间降水相关系数为0.62～0.993;(2)逐次抽站后,雨量站控制面积和邻近站间距离逐渐增大,邻近站点间降水相关系数逐渐减小;(3)抽站后站网面雨量与原站网面雨量较一致,误差较小,泰森多边形法面雨量变化幅度小于算术平均法;(4)从降水过程来看,各次抽站后,降水落区和各量级降水范围基本一致,站网对降水极值的捕捉能力较好,误差较小,但随着站点数的减少,对于降水形态刻画的精细程度有所下降。     

基于数据传输特性的卫星广播通道参数优化方法与应用

中国气象局卫星广播系统（CMACast）是全球对地观测广播系统（GEONETCast）框架下三大对地广播系统之一,在世界气象组织信息系统（WIS）和综合卫星数据分发服务系统(IGDDS)框架下,承担亚太地区气象数据广播分发的职责。随着气象业务的发展,广播系统数据量由180 GB/天增长至460 GB/天,在广播带宽资源有限而广播数据种类和大小各异的情况下,系统管理员越来越难以通过经验对广播通道参数调整以保持广播系统播发效率,造成部分通道数据播发时效下降严重,不能满足业务时效要求。通过对不同气象数据传输特性的定量分析,获得各类数据的精细化数据传输样本,在此基础上对各类数据广播通道参数进行科学、定量的计算和优化,使数据播发时效明显提升,应用到实际广播业务中效果明显。     

改进的单纯形法及其在非线性参数估计中的应用

采用了改进的单纯形法,该算法利用遗传算法的变异操作来增强单纯形法的全局搜索能力,既兼顾了全局收敛性,又具有高效的局部搜索能力。并通过实例验证了该算法的优越性,以及应用于测量上的非线性最小二乘估计的可行性。     

条带开采地表沉陷预计参数的确定

概率积分法是条带开采地表移动和变形预计常用的方法,而概率积分法预计的精度取决于其预计参数的确定。以国内大量的条带开采实测资料为基础,应用相似理论对条带开采地表沉陷的相似现象进行了模糊聚类分析,计算出了条带开采地表沉陷预计参数。根据所得条带开采地表沉陷相似现象的分类及其地表沉陷预计参数,应用模式识别对待求条带开采地表沉陷预计参数进行了求取。工程实例表明,用模糊优化确定的预计参数进行条带开采地表移动和变形预计,其预计结果更加可靠、准确。     

Vision-based tracking with projective mapping for parameter identification of remotely operated vehicles

Parameter identification of a remotely operated vehicle (ROV) is often based on the dynamic responses collected by its onboard sensors. However, for commercial ROVs, the required data for identification may not be available due to the absence of suitable sensors or limitations in accessing onboard sensor data. Therefore, this study proposes a vision-based tracking system to measure the dynamic response of an ROV. The tracking system is independent of the ROV, and is able to localize an ROV to a high degree of precision by means of projective mapping. The validity of the proposed tracking system is demonstrated through identification of a commercial ROV. A simplified nonlinear ROV dynamic model with six degrees of freedom (DOF) is used for identification. Uncoupled motions, including surge, sway, and yaw, are obtained from the ROV dynamic model, and the corresponding experiments are carried out for each DOF. Hydrodynamic parameters are then estimated with numerical optimizations by comparing the measured ROV responses with the output of the mathematical model. The experimental results show that the vision-based tracking system can accurately measure the transient and steady-state responses of an ROV. Additionally, the simulations of the ROV dynamic model, with the optimal parameter estimates, give results in agreement with the measured data.     

Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: Application to skipjack tuna

A Spatial Ecosystem and Population Dynamic Model (SEAPODYM) is used in a data assimilation study aiming to estimate model parameters that describe dynamics of Pacific skipjack tuna population on ocean-based scale. The model based on advection–diffusion–reaction equations explicitly predicts spatial dynamics of large pelagic predators, while taking into account data on several mid-trophic level components, oceanic primary productivity and physical environment. In order to improve its quantitative ability, the model was parameterized through assimilation with commercial fisheries data, and optimization was carried out using maximum likelihood estimation approach. To address the optimization task we implemented an adjoint technique to obtain an exact, analytical evaluation of the likelihood gradient. We conducted a series of computer experiments in order to (i) determine model sensitivity with respect to variable parameters and, hence, investigate their observability; (ii) estimate observable parameters and their errors; and (iii) justify the reliability of the computed solution. Parameters describing recruitment, movement, habitat preferences, natural and fishing mortality of skipjack population were analysed and estimated. Results of the study suggest that SEAPODYM with achieved parameterization scheme can help to investigate the impact of fishing under various management scenarios, and also conduct forecasts of a given species stock and spatial dynamics in a context of environmental and climate changes.     

Shape optimization of two-dimensional cavitators in supercavitating flows, using NSGA II algorithm

The reduction of energy consumption of high speed submersible bodies is an important challenge in hydrodynamic researches. In this paper, shape optimization of two-dimensional cavitators in supercavitating flows is studied. A two dimensional supercavitation potential flow passes a symmetric two dimensional cavitator, which is placed perpendicular to the flow in a channel of infinite length and immediately a cavity is formed behind the cavitator. This is because of the generation of a gas or vapor cavity between the body and the surrounding liquid due to the change in a high speed flow direction passing the cavitator. Drag force acting on this supercavitating body dictates the thrust requirements for the propulsion system, to maintain a required cavity at the operating speed. Therefore, any reduction in the drag force, by modifying the shape of the cavitator, will lead to decrease this force. This study concentrates on the optimization of two dimensional cavitators in order to decrease drag coefficient for a specified after body length and velocity in a potential flow. To achieve this goal a multi-objective optimization problem is defined to optimize cavitator shapes in supercavitating flow. The so-called NSGA II (Non-dominated Sorting Genetic Algorithm) algorithm is used as an optimization method. Design parameters and constraints are obtained according to supercavitating flow characteristics and cavitator modeling and objective functions are generated using Linear Regression Method. The obtained results are compared with other classic optimization methods, like the weighted sum method, for validation.     

一株海洋芽孢杆菌B09的筛选及其发酵条件优化研究

从海水养殖环境中筛选出一株具有较强抗菌活性的芽孢杆菌B09,并对其进行抗菌活性研究和发酵条件优化。结果显示B09对金黄色葡萄球菌、大肠杆菌、鳗弧菌等致病菌有较强抑制作用,其最佳发酵条件如下:KB培养基(蛋白胨20g,甘油10mL,K2HPO41.5g,MgSO4.7H2O1.5g,水1000mL),发酵温度32℃,发酵起始pH为7,发酵时间48h,250mL的三角瓶装量100mL,接种量1%。