地下水污染源反演的Hooke Jeeves吸引扩散粒子群混合算法

根据污染物质量浓度监测数据进行地下水污染源反演是一类典型的地下水逆问题,该问题可转化为决策变量为污染源位置和强度的最优化问题进行求解。基于Hooke-Jeeves粒子群混合算法,引入吸引扩散粒子群(ARPSO)算法的粒子群发散算子,保证混合算法的种群多样性,并提出HJ-ARPSO混合算法,再结合地下水污染物迁移模型MT3DMS反演地下水污染源的位置和强度信息。在已知污染源位置和未知污染源位置两种情形下,分别利用HJ-ARPSO算法、HJ-PSO算法和GA算法进行地下水污染源反演。在两种情形下,HJ-ARPSO算法均具有较高的寻优成功率(分别对应为100%和90%);与之相比,未引入粒子群发散算子的HJ-PSO算法在未知污染源位置情形下其寻优成功率迅速降为60%;GA算法寻优效率则最低。算例结果表明,HJ-ARPSO算法是一种有效的地下水污染源反演优化算法。     

Achieving to some outranking relationships between post mining land uses through mined land suitability analysis

Adoption of most suitable post mining land use is a problem with multi-dimensional nature. There are so many factors in this problem which seriously influence on the decision judgments. Therefore, in this study a fifty-attribute framework for mined land suitability analysis including fifty numbers of economical, social, technical and mine site factors developed to be a foundation for this decision making problem. Analysis by an outranking multi-attribute decision-making technique, called elimination et choix traduisant la realite method, was taken into consideration because of its clear advantages on the field of mined land suitability analysis as compared with multi-attribute decision-making ranking techniques. Analytical hierarchy process method applied to calculate global weights of the attributes through pair wise comparison matrixes. The weights then passed to the elimination et choix traduisant la realit method so that the most efficient post mining land uses could be appointed through comparisons of pair-wise dominance relationships between alternatives. This approach applied to an illustrative example where, final results showed that, there were two non-dominated land-uses for the considered example; industrial and pasture. However by increasing indifference threshold limit, the non-dominated set reduced to a single alternative that was pasture land-use.     

Robust approach for optimal positioning and ranking potential rainwater harvesting structure (RWH): a case study of Iraq

Rainwater harvesting (RWH) structure is considered as the best solution to conserve water for arid regions. The selection of RWH location is based on several key determinants such as hydrology, environment, topography, and socio-economic. This study proposed a robust methodology to identify and select the location of RWH using geographical information systems (GIS) and remote sensing (RS) with multi-criteria decision techniques in areas where data are scarce. Several thematic maps were extracted such as vegetation cover, soil group, slope, land use, and digital elevation (DEM). The RWH sites were ranked based on four major indexes: evaporation, cost-benefit, sediment, and hydrological index. Sensitivity analysis shows that the variance inverse (VI) and rank order method (ROM) considered all indices that effect ranking as compared to the analytic hierarchy process (AHP) and fuzzy-AHP. Sensitivity analysis also proved that the proposed method is suitable to be used for RWH site selection in arid regions.     

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.     

A new linguistic quantifier knowledge-guided OWA approach for mineral prospectivity mapping: a case study of the Bavanat Region,Iran

The main purpose of this study is to introduce a geographic information system (GIS)-based, multi-criteria decision analysis method for selection of favourable environments for Besshi-type volcanic-hosted massive sulphide (VHMS) deposits. The approach integrates two multi-criteria decision methods (analytical hierarchy process and ordered weighted averaging) and theory of fuzzy sets, within a GIS environment, to solve the problem of big suggested areas and missing known ore deposits in favourable environment maps for time and cost reduction. We doubled the fuzzy linguistic variables’ significance as a method to apply the arrange weights that the analytical hierarchy process (AHP)-ordered weighted averaging (OWA) hybrid procedure depends on. Another aim of this work is to assist mineral deposit exploration by modelling existing uncertainty in decision-making. Both AHP and fuzzy logic methods are knowledge-based, and they are affected by decision maker judgments. We used data-driven OWA approach in a hybrid method for solving this problem. We applied a new knowledge-guided OWA approach on data with changing linguistic variables according to the mineral system for VHMS deposits. Additionally, we used a vector-based method combination, which increased the precision of results. Results of knowledge-guided OWA showed that all of the mines and discovered deposits have been predicted with 100% accuracy in half of the size of the suggested area. To summarize, results improved the selection of possible target sites and increased the accuracy of results as well as reducing the time and cost, which will be used for field exploration. Finally, the hybrid methods with a knowledge-guided OWA approach have delivered more reliable results compared to exclusively knowledge-driven or data-driven methods. The study proved that expert knowledge and processed data (information) are critical important keys to exploration, and both of them should be applied in hybrid methods for reaching reliable results in mineral prospectivity mapping.     

Meta分析在矿集区成矿信息权重值比较中的应用

矿集区内隐伏矿综合定位预测方法已成为找矿预测领域的研究热点。矿床矿点的形成是由多种非线性成矿因素综合作用的结果,多属性模糊优选决策模型(FOMMAD)是解决这类问题的有效工具。寻找一个科学合理的属性权重确定方法,是FOMMAD能否成功实施的关键。首次应用Meta分析方法对地层、接触带、断裂、蚀变、构造交汇处5种找矿信息的权重进行了定量比较研究。在此基础上,运用FOMMAD及模糊层次分析法(FAHP),在研究区圈定了12个成矿有利度较高的靶区。验证结果表明,基于Meta分析与FOMMAD模型的多元找矿信息综合预测模型得到的成矿有利度可作为研究区找矿预测的综合标志。     

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.     

基于重磁数据梯度比值的深度学习技术实现场源位置反演方法

场源中心位置的计算是重磁数据反演的主要任务之一,现主要通过异常与场源位置之间的数学物理方程来估算地质体的位置.为了快速、准确获得地质体的位置信息,提出基于重磁梯度比值的深度学习技术实现场源位置的获取;其利用深度学习技术所建立的重磁梯度比值水平分布与地质体埋深、构造指数的关系,快速实现异常场源位置计算,且提出利用多个值的相互关系来更加准确、稳定地计算出地质体的信息.该方法可以计算复杂地质体的中心位置,且避免了以往线性方程反演方法需对结果进行筛选的复杂过程,对于存在剩磁的磁异常则采用解析信号的深度学习方法来进行位置反演.理论模型试验证明利用梯度比值的深度学习方法可以准确获得地质体的深度,且通过对比更多点的深度学习计算结果发现,采用多个不同比例极值点可以减弱噪声带来的干扰,从而得到更加准确的位置.最后将该方法应用于实测磁异常的反演工作,获得了地下磁性物体的中心位置,且计算结果与欧拉反褶积法相接近,因此该方法具有良好的实用性.      

抗震设防决策中的模糊信息处理

抗震设防决策过程中涉及到许多对整个分析过程都具有重要意义的模糊信息 ,本文提出一种结合模糊信息进行地震危险性概率分析与抗震设防决策的方法 ,介绍了用模糊集模拟模糊信息的原理 ,以及进一步处理模糊信息的区间分析顶点法。作为一例 ,这些方法结合基于泊松分布的地震烈度发生概率模型 ,应用于南京市区未来 5 0年的地震危险性与抗震设防效益分析 ,提供模糊的结论供设防决策参考。     

基于D-S证据理论的多水库联合调度方案评价

多水库防洪调度是一个典型的具有不确定性的多目标决策问题,在调度决策过程中,往往含有大量不确定性因素。提出了利用D-S证据推理方法,对多水库联合防洪调度方案进行评价。通过对不确定性评价信息进行融合,将问题转化为确定性决策问题。给出了证据合成的算法步骤,通过算例分析说明该方法的有效性和实用性。     

桩筏基础的系统模拟法优化设计研究

针对桩筏基础复杂的大系统问题,提出了系统模拟法优化设计思想。首先应用正交试验设计优化系统输入,其次采用桩筏基础有限元分析程序计算系统输出响应,最后运用多目标决策技术优化系统输出响应并确定桩筏基础优化设计均衡解。该方法实现了人机交互的优化设计,可确保优化结果可行性。     

复杂系统模糊模式识别动态规划模型研究

将模糊识别集合算子和非结构决策分析方法引入模糊动态规划中,推导出了两种求解复杂系统多目标多阶段决策问题的方法:级别特征值最小法和阶段模糊识别递推法。这两种方法具有不同的递推方程,可以应用于不同的情况,从而形成了模糊模式识别动态规划模型。此模型可以有效地获取和集成决策者的经验知识和偏好。此模型已应用到实践中,并取得良好效果。     

Simulation–Regression Approximations for Value of Information Analysis of Geophysical Data

Value of information analysis is useful for helping a decision maker evaluate the benefits of acquiring or processing additional data. Such analysis is particularly beneficial in the petroleum industry, where information gathering is costly and time-consuming. Furthermore, there are often abundant opportunities for discovering creative information gathering schemes, involving the type and location of geophysical measurements. A consistent evaluation of such data requires spatial modeling that realistically captures the various aspects of the decision situation: the uncertain reservoir variables, the alternatives and the geophysical data under consideration. The computational tasks of value of information analysis can be daunting in such spatial decision situations; in this paper, a regression-based approximation approach is presented. The approach involves Monte Carlo simulation of data followed by linear regression to fit the conditional expectation expression that is needed for value of information analysis. Efficient approximations allow practical value of information analysis for the spatial decision situations that are typically encountered in petroleum reservoir evaluation. Applications are presented for seismic amplitude data and electromagnetic resistivity data, where one example includes multi-phase fluid flow simulations.     

Stochastic response surface method for reliability problems involving correlated multivariates with non-Gaussian dependence structure: Analysis under incomplete probability information

This paper aims to provide a stochastic response surface method (SRSM) that can consider non-Gaussian dependent random variables under incomplete probability information. The Rosenblatt transformation is adopted to map the random variables from the original space into the mutually independent standard normal space for the stochastic surrogate model development. The multivariate joint distribution is reconstructed by the pair-copula decomposition approach, in which the pair-copula parameters are retrieved from the incomplete probability information. The proposed method is illustrated in a tunnel excavation example. Three different dependence structures characterized by normal copulas, Frank copulas, and hybrid copulas are respectively investigated to demonstrate the effect of dependence structure on the reliability results. The results show that the widely used Nataf transformation is actually a special case of the proposed method if all pair-copulas are normal copulas. The effect of conditioning order is also examined. This study provides a new insight into the SRSM-based reliability analysis from the copula viewpoint and extends the application of SRSM under incomplete probability information.     

ICT-Based Remediation with Knowledge Information Management for Contaminated Groundwater

ICT-based remediation with knowledge information management is presented for the pump-and-treat method of contaminated groundwater. The usefulness of ICT is discussed for monitoring contaminants and groundwater level, transferring data between the remediation well and the remote remediation center, and decision support analysis for controlling the remediation well. A prototype system was developed and applied to field measurement. The prototype system performed reliably for ~600 days. As a decision support analysis, a fuzzy inference model is discussed. The membership functions were determined based on simple reliability theory. The effectiveness of the proposed method was assessed by numerical simulations. The simulation results suggest that the proposed method is likely to reduce the pumped quantity compared to PID control or an engineer’s empirical knowledge. Analysis results are also shown for cancer risks from contaminants and ground settlement risks due to excess pumping up of groundwater.     

多地震属性体实时融合三维可视化技术

多属性融合技术是近年来针对单一属性的局限性而发展起来的一项新技术。通过研究三维空间中多种地震属性体实时融合技术,提出了一种实现方案。采用八叉树结构有效进行数据的动态管理,基于Shader编程技术,利用GPU可编程管线加速,实现多属性体融合的三维可视化。基于该方案,研发了三维可视化多属性体融合系统,实现了基于RGB映射和属性加权的两种融合技术,保证了多属性体高质量实时融合渲染,通过实际应用取得了良好效果。     

边坡治理群决策的二维足码定位法研究

在边坡治理决策过程中,不仅涉及边坡本身的条件和状态等因素,而且涉及经济、技术、环境及专家和决策者的个人素质等因素,因此边坡治理方案选择是一个复杂的系统工程。在实际工程中,往往同时有几个治理方案供选择,必须对它们进行优化评价,从中选出较满意的方案。针对边坡治理方案评价是一个群决策问题,提出了边坡治理群决策的二维足码定位法,利用简单的二维足码坐标图或评价函数,可以确定边坡治理的最优方案。以溪沟口滑坡治理为例,分析了该方法的实际应用情况。     

Hybrid spatial data mining methods for site selection of emergency response centers

Traditional methods for site selection fail to give reasonable weight to the potential risk grade of different locations. Consequently, site selection does not highlight locations with higher risk grades. Thus, a hybrid analytical method for the site selection of emergency response centers is proposed. First, spatial predicates are incorporated into emergency event analysis. These spatial predicates describe the spatial relationships between emergency locations and surrounding objects. A spatial data association mining method is then developed to identify the correlation rules that contain emergency information and geographical factors. Such rules act as the weight adding mechanism on different urban buildings, such that every spatial object is assigned a risk grade based on these rules. Furthermore, a simulated annealing algorithm is developed by incorporating the weight adding method to locate the optimal sites for emergency centers. A series of experiments is conducted, and the results demonstrate the efficiency of the proposed hybrid method.     

Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.     

Using fuzzy TOPSIS method for mineral processing plant site selection

Site selection for the mineral processing is the most important decision made by owner that has a significant impact on the efficiency of the whole process. This is a critical decision which involves considering a number of criteria and finding the best location among feasible alternatives. Therefore, a multicriteria decision-making method is necessary to apply site-selection process to find the best location that meet desired conditions set by the selection criteria. This paper presents an application of TOPSIS method based on fuzzy sets (fuzzy TOPSIS), which is one of the broader multicriteria decision making means, used to select an appropriate site for mineral processing plant for Sangan iron ore mine (phase 2). For this purpose, at first considering the geological, technical, economical, and environmental factors, three feasible alternatives were selected for the processing plant using Geographical Information System. Then, based on the technical and experimental experiences and through judgment of the decision makers and experts, 14 criteria were established and these alternatives were evaluated. Finally, the alternatives were ranked and the best location was recommended.