Spatially enabled emergency event analysis using a multi-level association rule mining method

Spatial attributes are important factors affecting the entire process of emergency management. Despite the importance of spatial attributes in emergency rescue, this subject has not been subjected to thorough examination in previous literature. This paper presents a new method that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. More specifically, we developed three mechanisms to achieve spatially enabled emergency analysis. First, a novel fact constellation schemas that integrate the spatial predicates and non-spatial data of emergency events is created for multi-level analysis. Second, a filtering algorithm is designed to remove redundant predicates from the huge amount of spatial predicates for data association rule mining. Third, by incorporating the filtering method, a multi-level spatial data association algorithm was proposed to realize the analytical function for emergency events. Experiments were conducted, and the results validate the effectiveness of our method.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

Industrial structure,technological progress and CO<Subscript>2</Subscript> emissions in China: Analysis based on the STIRPAT framework

The application of facility location problems in choosing the best location of relief distribution centers plays a salient role in emergency operations of large-scale disasters. On the premise that the service recipients are uniformly distributed along the network edges, this study investigates a combined mobile and immobile pre-earthquake facility location problem. A predefined number of locations are to be selected among a set of potential locations. Each facility is used in the relief distribution operation. It is incontrovertible that due to earthquakes, some network edges collapse and corresponding areas may lose their accessibility. Thus in this study, it is assumed that people on intact and accessible edges travel to the location of the distribution centers to receive the relief. For those who are located on collapsed or inaccessible network edges, the medium-scale unmanned aerial vehicle (UAV) helicopters are utilized in the relief distribution operation. This study aims to develop a mathematical model which minimizes the aggregate traveling time for both people and UAVs over a set of feasible scenarios. Since the network problems are NP-hard, some metaheuristic algorithms are developed to solve the proposed model. In order to demonstrate the applicability of developed model, a case study based on feasible earthquake scenarios in Tehran is presented.     

Kriging插值方法在地层模型生成中的应用

为了建立三维数字地层,采用了一种适合城市工程地质和岩土工程特点的地层数据模型-基于钻孔信息的3棱柱模型。由于钻孔之间的距离稀疏程度、方向、数据值存在差异,钻孔以外未知的地质特性需要插值和推断,传统的数理统计方法无法很好地解决空间样本点的选取、空间估值和2组以上空间数据的关系等问题。借鉴地质统计学的Kriging方法给出一种距离加权插值算法,即先根据空间数据得到统计特征,再根据统计特征进行插值。通过对地层模型插值结果的观察,得出该算法可以获得良好的插值效果。     

A hybrid method for grade estimation using genetic algorithm and neural networks

In the present paper, a new hybrid method is proposed for grade estimation. In this method, the multilayer perceptron (MLP) network is trained using the combination of the Levenberg–Marquardt (LM) method and genetic algorithm (GA). Having a few samples for grade estimation, it is difficult to get a proper result using some function approximation methods like neural networks or geostatistical methods. The neural network training methods are very sensitive to initial weight values when there are a few samples as a training dataset. The main objective of the proposed method is to resolve this problem. Here, our method finds the optimal initial weights by combining GA and LM method. Having the optimal initial values for weights, the local minima are avoided in the training phase and subsequently the neural network sustainability is trained optimally. Furthermore, the hybrid method is applied for grade estimation of Gol-e-Gohar iron ore in south Iran. The proposed method shows significant improvements compared to both conventional MLP and Kriging method. The efficiency of the proposed method gets more highlighted when the training data set is small.     

一种基于三角网的地质体三维模型切割方法

三维地质体模型相交元素之间构成的奇异空间关系与复杂的模型要素形态极大影响了切割算法稳健性及切割结果可靠性.提出一种几何运算与关系表达相统一的地质体三维模型切割算法.算法首先构建交点对象拓扑结构,存储交点与所在三角形单元及空间邻近要素的相对位置关系;然后结合精确谓词法设计完整的边-三角形相交类型分类图,记录27种相交情况与交点位置的对应关系,并在重三角化过程中建立交点调整机制,利用交点对象拓扑结构中关联的空间关系作为上下文约束,有效控制投影降维浮点误差带来的交点位置偏差的不良影响.实验结果表明,算法能够有效处理地质体模型中的三角网退化/近似退化、自相交及共面/近似共面等奇异空间关系,同时具有良好的运算效率.      

Selection of emergency shelter sites for seismic disasters in mountainous regions: Lessons from the 2008 Wenchuan Ms 8.0 Earthquake,China

In this paper, we use the 12 May 2008 Wenchuan Earthquake as a background event for analyzing and applying the principles of site selection of emergency shelters for a disastrous earthquake. Based on field investigations and analyses of remote sensing imagery, we identified the distribution of active faults and the locations of co-seismic surface rupture zones—areas in which buildings are at risk of intensive damage. It is important that emergency shelters are located outside of such vulnerable areas. One of the lessons learned from the Wenchuan Earthquake is that high fatality rates occur in areas without life-saving shelters. The principles that underlie the selection of emergency shelter sites are as follows: (1) keep far away from active fault zones, with the distance depending on the characteristics of the fault, including the nature of hangingwall and footwall structures; (2) disaster-mitigation strategies should be developed as a multi-dimensional system for the management of natural hazards, human activities, and urban expansion, involving keeping away from vulnerable slopes and establishing an early-warning system; (3) the accessibility of mountainous regions must be considered, including establishing small emergency shelters that house large numbers of people and covering regions with an uneven distribution of villages; and (4) government and law-making agencies in China must establish new earthquake design codes for buildings, emphasizing the importance of public facilities (including schools, collective welfare institutions, and medical facilities) as emergency shelters during disastrous earthquakes. The site-selection process requires an interdisciplinary approach involving seismologists, engineers, environmental and social scientists, emergency management personnel, and government officials. The parameters upon which the above principles are based can be qualitatively determined, thereby providing a valuable initial database for further quantitative analysis. The preliminary results and knowledge gained in the present paper can be used as a decision-making tool to support the government in earthquake-recovery and reconstruction programs. We also discuss practical examples of site evaluation in regions that suffered heavy damage during the Wenchuan Earthquake.     

Landfill site selection based on reliability concepts using the DRASTIC method and AHP integrated with GIS – a case study of Bengaluru city,India

The selection of landfill sites for municipal solid waste (MSW) disposal involves consideration of geological, hydrological and environmental parameters which exhibit large spatial variability. Therefore, it is necessary to define, to what extent the chosen sites are reliable such that the probability of environmental pollution and health risks to population is minimal. In the present study, groundwater vulnerability to contamination has been assessed using the standard DRASTIC method. The results showed that the study region has 9.45% of very less, 32.94% of less, 25.47% of moderate, 22.79% of high and 9.35% of very high vulnerable zones. The study also revealed that none of the landfills are located in safe zones. This suggests that it requires proper remedial measures to avoid environmental pollution. A landfill site selection process has been carried out using the Analytical Hierarchy Process integrated with Geographical Information System tools. The obtained results showed that only 3.59?km² (0.08%) of the total area is suitable for landfills. The reliability analysis of the site suitability revealed that landfills are located at unreliable locations where the probability of risk to environmental pollution is high. The presented approach assists decision-makers in selecting reliable locations for the safe disposal of MSW.     

地质条件不确定性下TBM管片结构失事概率计算

不良地质条件是影响TBM施工隧洞管片结构安全的重要因素。综合考虑围岩地质条件和衬砌结构的不确定性,提出了一种定量分析TBM管片结构失事概率的新方法。在基于Markov过程估计隧洞沿程地质岩性变化概率的基础上,建立了隧洞任意位置处管片选型不匹配的概率模型;考虑围岩和管片参数的不确定性,采用随机有限元方法计算某一类型管片在不同围岩下的失事概率;由此,采用全概率公式,可计算隧洞沿程任意位置处管片结构的失事概率。结合实际工程,针对施工期工况,确定了该隧洞管片沿程的失事概率、最大失事概率及其所对应的位置等,为管片选型、优化设计及TBM施工期的风险防范提供了依据。     

Localised Uniform Conditioning (LUC): A New Approach for Direct Modelling of Small Blocks

Recoverable mineralisation at a given mining selectivity is traditionally modelled from sparse data grids by non-linear geostatistical techniques such as Uniform Conditioning. This method estimates the tonnage and grade of mineralisation which can be extracted as small selective minable blocks from large blocks (panels), whose grade is modelled by Ordinary Kriging. Uniform Conditioning technique estimates the proportions of recoverable mineralisation in each panel without specifying the actual locations of the economically extractable blocks. This inability to predict a spatial location of the recoverable mineralisation is a major disadvantage of the conventional Uniform Conditioning method. A new approach, called Localised Uniform Conditioning, has been developed to overcome this limitation. This method applies the grade–tonnage relationships modelled by the Uniform Conditioning technique to the spatial grade distribution patterns approximated by direct kriging of the small blocks from the sparse data grid. This approach estimates localised selective mining units grades conforming to the proper grade–tonnage curves obtained by the Uniform Conditioning method as well as maintaining the relative spatial grade distribution pattern indicated by the directly kriged small block grades. The advantage of this approach is essentially dependent upon the data available for ranking the small blocks within a panel in increasing order of their grade. Ordinary Kriging of the small blocks can be used for their ranking providing the kriged estimates produce a meaningful indication of the relative grade pattern. Where the data is sparse and not close to a panel, or their distribution is characterised by a strong short-range variability, the advantages of using the Localised Uniform Conditioning approach are more limited.     

干热岩勘查开发工程场地选址评价指标体系研究

干热岩是储量大、用途广的新型、可再生绿色能源,对其进行开发利用意义重大。就我国现状而言,寻找适宜的干热岩勘查开发工程场地是成功实现干热岩开发利用的关键。从干热岩工程开发亟待解决的选址问题出发,系统地总结了国内外干热岩勘查开发的选址经验,从资源、技术、安全和经济4个方面建立了包含4个指标层共20个指标的干热岩勘查开发工程场地选址评价指标体系; 基于层次分析法,计算了各评价指标的权重,并提出了基于层次分析-综合评分法的干热岩勘查开发工程场地选址评价方法。该指标体系和评价方法对干热岩勘查开发工程场地选址具有一定指导意义。     

A model for the representation of emergency cases

The aim of this paper is to propose a location model of earthquake emergency service depot on the basis of hybrid multi-attribute decision-making method. The advantage of the proposed method is that practical mixed uncertainty of location decision information is considered, and the corresponding factors that affect the location of transfer stations are contained. To solve the location problem, a hybrid multi-attribute decision procedure without information transformation is developed. Besides, a novel weighting method and aggregation process is given. Finally, a numerical example is provided to show the feasibility and validity of the proposed method.     

Emergency alternative evaluation and selection based on ANP,DEMATEL, and TL-TOPSIS

With the increasing occurrence frequency of emergency events, emergency management (EM) has been a very important issue in management science. One of the major activities of EM is to evaluate and select the most desirable emergency alternative(s). This paper proposes a new framework combining the analytic network process (ANP) method, the decision-making trial and evaluation laboratory (DEMATEL) technique, and 2-tuple linguistic technique for order preference by similarity to an ideal solution (TL-TOPSIS) method to solve the emergency alternative evaluation and selection problem. This study has been done in three stages. In the first stage, we use DEMATEL technique to obtain the network relation map (NRM) among emergency alternative evaluation criteria or sub-criteria. In the second stage, we use ANP method to calculate the global weight of each sub-criterion based on the NRM among emergency alternative evaluation sub-criteria. In the third stage, the ratings of emergency alternative with respect to each sub-criterion are described by linguistic items, and the TL-TOPSIS method is used to rank the emergency alternative. Finally, a practical example of urban fire emergency alternative selection is given to illustrate the application of the proposed framework.

     

Emergency alternative evaluation and selection based on ANP,DEMATEL, and TL-TOPSIS

With the increasing occurrence frequency of emergency events, emergency management (EM) has been a very important issue in management science. One of the major activities of EM is to evaluate and select the most desirable emergency alternative(s). This paper proposes a new framework combining the analytic network process (ANP) method, the decision-making trial and evaluation laboratory (DEMATEL) technique, and 2-tuple linguistic technique for order preference by similarity to an ideal solution (TL-TOPSIS) method to solve the emergency alternative evaluation and selection problem. This study has been done in three stages. In the first stage, we use DEMATEL technique to obtain the network relation map (NRM) among emergency alternative evaluation criteria or sub-criteria. In the second stage, we use ANP method to calculate the global weight of each sub-criterion based on the NRM among emergency alternative evaluation sub-criteria. In the third stage, the ratings of emergency alternative with respect to each sub-criterion are described by linguistic items, and the TL-TOPSIS method is used to rank the emergency alternative. Finally, a practical example of urban fire emergency alternative selection is given to illustrate the application of the proposed framework.     

Risk evaluation of China’s natural disaster systems: an approach based on triangular fuzzy numbers and stochastic simulation

To deal effectively with the evaluation problem of natural disaster risk system affected by many uncertain factors, a multivariate connection number expression is presented. This expression is based on the index samples and evaluation grade criterions of natural disaster risk system and is capable of describing the hierarchy property and fuzziness of membership relationship between index samples and evaluation grade criterions. In this proposed method, the fuzzy evaluation grade criterion problem is resolved by combining triangular fuzzy numbers with multivariate connection number theory, and triangular fuzzy numbers are used to express the discrepancy degree coefficients of connection number and evaluation index weights. Accordingly, a connection number-based evaluation method for the natural disaster system of China (named CN-TFN for short) is established using triangular fuzzy numbers and stochastic simulation. The application results show that the spatial distribution of natural disaster risk grades of China has the trend of aggrandizement from west to east of China. The economically developed and densely populated coastal areas are very likely to have a high level of natural disaster risk grade or above; thus, these areas are the key regions of the natural disaster risk management of China. The results also show that the CN-TFN is able to reflect practical conditions of the evaluation problem of natural disaster system and to provide more reliability information as compared to the existing evaluation methods. This is as a result of its comprehensive usage of various information of subjective and objective uncertainties in the evaluation process of natural disaster risk system and its expression by confidence intervals. Due to the simplicity and generalization, the CN-TFM is applicable to comprehensive risk grade evaluation of various natural disaster systems.     

Optimally locating additional drill holes in three dimensions using grade and simulated annealing

Average kriging variance is a standard tool used in optimization of the location of additional drill holes. However, this tool cannot distinguish between areas with different priorities. This limitation could be eliminated by using weighted average kriging variance. This paper extends the problem of optimal location to three dimensional cases, use grade as a weight and search optimum locations by simulated annealing. Weighted average kriging variance is used as objective function. The method is applied to a copper deposit. Results have shown that weighting of the estimation variance with ??grade?? is effective only when the difference among the grades estimated for different blocks is considerable.     

Non-parametric machine learning methods for interpolation of spatially varying non-stationary and non-Gaussian geotechnical properties

Spatial interpolation has been frequently encountered in earth sciences and engineering.A reasonable appraisal of subsurface heterogeneity plays a significant role in planning,risk assessment and decision making for geotechnical practice.Geostatistics is commonly used to interpolate spatially varying properties at un-sampled locations from scatter measurements.However,successful application of classic geostatistical models requires prior characterization of spatial auto-correlation structures,which poses a great challenge for unexperienced engineers,particularly when only limited measurements are available.Data-driven machine learning methods,such as radial basis function network(RBFN),require minimal human intervention and provide effective alternatives for spatial interpolation of non-stationary and non-Gaussian data,particularly when measurements are sparse.Conventional RBFN,however,is direction independent(i.e.isotropic)and cannot quantify prediction uncertainty in spatial interpolation.In this study,an ensemble RBFN method is proposed that not only allows geotechnical anisotropy to be properly incorporated,but also quantifies uncertainty in spatial interpolation.The proposed method is illustrated using numerical examples of cone penetration test(CPT)data,which involve interpolation of a 2D CPT cross-section from limited continuous 1D CPT soundings in the vertical direction.In addition,a comparative study is performed to benchmark the proposed ensemble RBFN with two other non-parametric data-driven approaches,namely,Multiple Point Statistics(MPS)and Bayesian Compressive Sensing(BCS).The results reveal that the proposed ensemble RBFN provides a better estimation of spatial patterns and associated prediction uncertainty at un-sampled locations when a reasonable amount of data is available as input.Moreover,the prediction accuracy of all the three methods improves as the number of measurements increases,and vice versa.It is also found that BCS prediction is less sensitive to the number of measurement data and outperforms RBFN and MPS when only limited point observations are available.     

地理信息系统GIS支持下的城市地质环境评价

以 GIS为支撑工具 ,对城市地质环境空间数据库的建立方法、城市建设用地类型的初步划分及城市建设用地与地质环境的协调性评价模型作了分析 ,并选取典型实例进行剖析 ,结果表明 GIS是城市地质环境研究的有效工具。     

Site selection for managed aquifer recharge using fuzzy rules: integrating geographical information system (GIS) tools and multi-criteria decision making

One of the most important water-resources management strategies for arid lands is managed aquifer recharge (MAR). In establishing a MAR scheme, site selection is the prime prerequisite that can be assisted by geographic information system (GIS) tools. One of the most important uncertainties in the site-selection process using GIS is finite ranges or intervals resulting from data classification. In order to reduce these uncertainties, a novel method has been developed involving the integration of multi-criteria decision making (MCDM), GIS, and a fuzzy inference system (FIS). The Shemil-Ashkara plain in the Hormozgan Province of Iran was selected as the case study; slope, geology, groundwater depth, potential for runoff, land use, and groundwater electrical conductivity have been considered as site-selection factors. By defining fuzzy membership functions for the input layers and the output layer, and by constructing fuzzy rules, a FIS has been developed. Comparison of the results produced by the proposed method and the traditional simple additive weighted (SAW) method shows that the proposed method yields more precise results. In conclusion, fuzzy-set theory can be an effective method to overcome associated uncertainties in classification of geographic information data.