Estimating spatial efficiency using cyber search,GIS, and spatial optimization: a case study of fire service deployment in Los Angeles County

ABSTRACT

The efficiency of public investments and services has been of interest to geographic researchers for several decades. While in the private sector inefficiency often leads to higher prices, loss of competitiveness, and loss of business, in the public sector inefficiency in service provision does not necessarily lead to immediate changes. In many cases, it is not an entirely easy task to analyze a particular service as appropriate data may be difficult to obtain and hidden in detailed budgets. In this paper, we develop an integrative approach that uses cyber search, Geographic Information System (GIS), and spatial optimization to estimate the spatial efficiency of fire protection services in Los Angeles (LA) County. We develop a cyber-search process to identify current deployment patterns of fire stations across the major urban region of LA County. We compare the results of our search to existing databases. Using spatial optimization, we estimate the level of deployment that is needed to meet desired coverage levels based upon the location of an ideal fire station pattern, and then compare this ideal level of deployment to the existing system as a means of estimating spatial efficiency. GIS is adopted throughout the paper to simulate the demand locations, to conduct location-based spatial analysis, to visualize fire station data, and to map model simulation results. Finally, we show that the existing system in LA County has considerable room for improvement. The methodology presented in this paper is both novel and groundbreaking, and the automated assessments are readily transferable to other counties and jurisdictions.     

Optimal routing for waste collection: a case study in Singapore

ABSTRACT

To collect and dispose growing amounts of municipal solid waste (MSW) changed to be a hot topic along with the rapid urbanization in past decades. Cities are more and more dependent on the incineration instead of landfilling due to the cost-efficiency and environmental concerns. Considering the limited number of incineration plants and complicated situation of transportation in both spatial and temporal dimensions in different cities, the optimal routing for waste collection turns to be meaningful research topic. In this research, the ant colony optimization (ACO)-based multi-objective routing model coupled with min-max model and Dijkstra’s algorithm is proposed to address the question of which route to take from these waste-generating points to the target incineration plant(s) considering travel time, accident probability (black spots), and population exposure, so as to support the routing decision-making. The model is successfully implemented in Singapore and the effectiveness of the model has also been justified. Besides, few limitations of this research have also been discussed, some of which would also be the future directions of our research, especially the design and integration of a web-based routing decision-making support system.     

页岩气基础地质调查皖南地1井钻探施工技术

皖南地1井是部署在安徽省南陵县烟墩镇的一口页岩气基础地质调查井。文章详细介绍了该井的钻探施工工艺技术以及遇到复杂问题的处理方法,并对钻效进行了分析,提出了实现优质高效钻探的措施。项目的顺利实施,梳理了皖南地区地层层序,为页岩气储层理论推测提供了有力的实物数据支撑和验证。     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.     

青藏高原复杂地层地质钻探低固相冲洗液试验研究

青藏高原由于地质条件的多样性,分布有松散破碎地层、高应力地层、断层破碎带等复杂地层,在地质钻探中经常遇到塌孔、漏浆、缩径、卡钻、埋钻等问题。同时配套使用的冲洗液形成的泥皮质量差、胶结能力较差、携岩粉能力较弱等不足。冲洗液的性能是实现复杂地层顺利钻进的关键。结合青藏高原复杂地层的地质特点,研发了低固相聚合物新型冲洗液,该冲洗液以钠质膨润土和微泡剂等外加剂为基础,具有流动性好、胶结性强、降失水量适中的特点,适宜在青藏高原复杂地层地质钻探中使用。     

基于优化经验模态分解和聚类分析的滑坡位移智能预测研究

针对三峡库区"阶跃式"滑坡的变形特征,提出了一种新的滑坡位移预测方法。以白水河滑坡ZG118和XD-01监测点位移数据为例,采用基于软筛分停止准则的经验模态分解(SSSC-EMD)将累计位移-时间曲线和影响因子时间序列自适应地分解为多个固有模态函数(IMF),并采用K均值(K-Means)聚类法对其进行聚类累加,得到有物理含义的位移分量(趋势性位移、周期性位移以及随机性位移)和影响因子分量(高频影响因子和低频影响因子)。使用最小二乘法对趋势性位移进行拟合预测;采用果蝇优化-最小二乘支持向量机(FOA-LSSVM)模型对周期性位移和随机性位移进行预测。将各位移分量预测值进行叠加处理,实现滑坡累计位移的预测。研究结果表明,所提出的(SSSC-EMD)-K-Means-(FOA-LSSVM)模型能够预测"阶跃式"滑坡的位移变化规律,且预测精度高于传统的支持向量机回归(SVR)、最小二乘支持向量机(LSSVM)模型;并通过改变训练集长度,进行单因素分析,发现其与预测精度之间呈正相关关系。     

下二门油田H2Ⅲ油组交联聚合物驱后油藏剩余油分布特征

微观驱油试验表明,交联聚合物驱后剩余油进一步减少,主要以斑块状、小油滴状等形态分布于微孔隙中;数值模拟显示,下二门油田H2Ⅲ油组交联聚合物驱后80.8%的面积已为中强水淹,纵向上79.7%的剩余油分布于主力油层.受构造、储层物性及井网因素控制,未淹、弱水淹剩余油平面上主要分布在断层附近、断层破碎带、微构造高点和砂体上倾尖灭区等部位;纵向上主要分布于低渗透层段.针对剩余油分布特征,通过完善注采关系、优化注采结构,单元含水量的上升速度和产量递减幅度得到控制,采收率在交联聚合物驱的基础上进一步提高了2.01%.     

GNSS控制网方案优化与数据处理分析

GNSS布设平面控制网已在工程项目中得到广泛应用.获得满意的平差结果的前提条件为:①高质量的基线数据;②约束GNSS控制网的已知点精度足够高,使得GNSS控制网的整体精度不受已知点约束而有明显改变;③优化的平差方案;④科学严密的平差模型.通过对某项目GNSS控制网的布设进行优化设计,并利用不同软件对观测数据进行处理分析...     

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.