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1.
In this study, a fuzzy-boundary interval-stochastic programming (FBISP) method is developed for planning water resources management systems under uncertainty. The developed FBISP method can deal with uncertainties expressed as probability distributions and fuzzy-boundary intervals. With the aid of an interactive algorithm woven with a vertex analysis, solutions for FBISP model under associated α-cut levels can be generated by solving a set of deterministic submodels. The related probability and possibility information can also be reflected in the solutions for the objective function value and decision variables. The developed FBISP is also applied to water resources management and planning within a multi-reservoir system. Various policy scenarios that are associated with different levels of economic consequences when the pre-regulated water-allocation targets are violated are analyzed. The results obtained are useful for generating a range of decision alternatives under various system conditions, and thus helping decision makers to identify desired water resources management policies under uncertainty.  相似文献   

2.
How to select a limited number of strong ground motion records (SGMRs) is an important challenge for the seismic collapse capacity assessment of structures. The collapse capacity is considered as the ground motion intensity measure corresponding to the drift‐related dynamic instability in the structural system. The goal of this paper is to select, from a general set of SGMRs, a small number of subsets such that each can be used for the reliable prediction of the mean collapse capacity of a particular group of structures, i.e. of single degree‐of‐freedom systems with a typical behaviour range. In order to achieve this goal, multivariate statistical analysis is first applied, to determine what degree of similarity exists between each selected small subset and the general set of SGMRs. Principal Component analysis is applied to identify the best way to group structures, resulting in a minimum number of SGMRs in a proposed subset. The structures were classified into six groups, and for each group a subset of eight SGMRs has been proposed. The methodology has been validated by analysing a first‐mode‐dominated three‐storey‐reinforced concrete structure by means of the proposed subsets, as well as the general set of SGMRs. The results of this analysis show that the mean seismic collapse capacity can be predicted by the proposed subsets with less dispersion than by the recently developed improved approach, which is based on scaling the response spectra of the records to match the conditional mean spectrum. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

3.
Several risk factors associated with the increased likelihood of healthcare-associated Clostridium difficile infection (CDI) have been identified in the literature. These risk factors are mainly related to age, previous CDI, antimicrobial exposure, and prior hospitalization. No model is available in the published literature that can be used to predict the CDI incidence using healthcare administration data. However, the administrative data can be imprecise and may challenge the building of classical statistical models. Fuzzy set theory can deal with the imprecision inherent in such data. This research aimed to develop a model based on deterministic and fuzzy mathematical techniques for the prediction of hospital-associated CDI by using the explanatory variables controllable by hospitals and health authority administration. Retrospective data on CDI incidence and other administrative data obtained from 22 hospitals within a regional health authority in British Columbia were used to develop a decision tree (deterministic technique based) and a fuzzy synthetic evaluation model (fuzzy technique based). The decision tree model had a higher prediction accuracy than that of the fuzzy based model. However, among the common results predicted by two models, 72 % were correct. Therefore, this relationship was used to combine their results to increase the precision and the strength of evidence of the prediction. These models were further used to develop an Excel-based tool called C. difficile Infection Incidence Prediction in Hospitals (CDIIPH). The tool can be utilized by health authorities and hospitals to predict the magnitude of CDI incidence in the following quarter.  相似文献   

4.
Multi-criteria analysis techniques are well known decision support methods and are widely applied in various disciplines. However, defining the input criteria values for the basic decision matrix which contains all criteria values for every alternative considered is normally not an easy task. Especially qualitative criteria variables which are frequently represented as linguistic terms may be hard to quantify. Moreover, some criteria cannot be represented by just one crisp value, but they may offer a range of possible values. Stochastic multi-criteria approaches which call for distribution models instead of single numerical values can be used in these cases. Outranking multi-criteria methods proved that simulation based stochastic techniques are well suited to give better insight into the preference structure of a variety of decision alternatives. However, besides the knowledge of the preference structure, it is also important to find out about the similarity of decision alternatives which allows a modeller to categorize a decision alternative as a really unique option or as just one option out of a greater subset of very similar alternatives. To be able to perform this categorization, principal components analysis (PCA) was used. The results of the PCA are compared to the results of a stochastic outranking analysis.  相似文献   

5.
In this study, a methodology for clustering 18 lakes in Alberta, Canada using the data of 19 water quality parameters for a period of 11 years (1988–2002) is presented. The methods consist of (i) principal component analysis (PCA) to determine the dominant water quality parameters, (ii) cluster analysis techniques to develop the characteristics of the clusters, and (iii) pattern‐match lakes to determine the appropriate cluster for each of the lakes. The PCA revealed that three principal components (PCs) were able to explain ～88% of the variability and the dominant water quality parameters were total dissolved solids, total phosphorus, and chlorophyll‐a. We obtained five clusters for the period 1994–1997 by using the dominant parameters with water quality deteriorating as the cluster number increased from 1 to 5. Upon matching cluster patterns with the entire dataset, it was observed that some of the lakes belonged to the same cluster all the time (e.g., cluster 1 for lakes Elkwater, Gregg, and Jarvis; cluster 3 for Sturgeon; cluster 4 for Moonshine; and cluster 5 for Saskatoon), while others changed with time. This methodology could be applied in other regions of the world to identify the most suitable source waters and prioritize their management. It could be helpful to analyze the natural controlling processes, pollution types, impact of seasonal changes and overall quality of source waters. This methodology could be used for monitoring water bodies in a cost effective and efficient way by sampling only less number of dominant parameters instead of using a large set of parameters.  相似文献   

6.
利用数据挖掘技术识别深层火山岩气层   总被引：4，自引：2，他引：2       下载免费PDF全文
石炭系火山岩的低渗透气藏具有的埋藏深、成因复杂、类型多、分布广、三孔隙度曲线响应特征不明显等特点,并且主要的四种火山岩气藏：玄武岩、安山岩、英安岩、流纹岩的密度和纵波时差测井值差别较大,因此使基于三孔隙度测井资料的一系列识别气层的有效方法在该盆地石炭系火山岩气层的识别中无明显效果.数据挖掘技术从数据的角度出发,在进一步丰富岩心、测井和试油资料的前提下,利用数据挖掘技术中的聚类分析和关联分析获取核心参数和数据之间的内在联系,用决策树提取预测火山岩气层的模型.该方法充分利用已有的数据资料,用数学分析方法遍历寻找对识别火山岩气层有用的信息,而不仅仅依靠三孔隙度和电阻率曲线,并且消除了岩性的影响,因此获得了较高的识别率.  相似文献   

7.
Hydro-economic models: Concepts, design, applications, and future prospects   总被引：6，自引：0，他引：6  
Future water management will shift from building new water supply systems to better operating existing ones. The variation of water values in time and space will increasingly motivate efforts to address water scarcity and reduce water conflicts. Hydro-economic models represent spatially distributed water resource systems, infrastructure, management options and economic values in an integrated manner. In these tools water allocations and management are either driven by the economic value of water or economically evaluated to provide policy insights and reveal opportunities for better management. A central concept is that water demands are not fixed requirements but rather functions where quantities of water use at different times have varying total and marginal economic values. This paper reviews techniques to characterize the economic value of water use and include such values in mathematical models. We identify the key steps in model design and diverse problems, formulations, levels of integration, spatial and temporal scales, and solution techniques addressed and used by over 80 hydro-economic modeling efforts dating back 45-years from 23 countries. We list current limitations of the approach, suggest directions for future work, and recommend ways to improve policy relevance.  相似文献   

8.
基于Abaqus软件的并行计算集群平台构建与优化方法   总被引：1，自引：0，他引：1  
根据有限元显式算法和隐式算法的特点,研究了岩土工程动力分析并行计算集群系统的硬件要求、集群系统的构建方法,构建了基于EM64T硬件构架、双路Intel Xeon处理器、Linux操作系统和64位Abaqus软件的32CPU并行计算集群平台,测试了存储子系统对集群性能的影响,比较了两种千兆以太网络作为、集群子网络的性能优化方法。以地下结构的地震反应分析为例,测试了优化前后该集群系统的计算速度,发现两种以太网络性能优化方法都可以有效提高集群计算速度。列举了该集群系统在深水桥梁基础流固耦合动力分析、地下结构地震反应分析和快速轨道交通环境振动分析中的应用,显示了该集群在显式算法、隐式算法及小规模、大规模数值计算问题中的并行计算效率,证明所构建的Abaqus数值模拟并行计算集群平台能够满足计算规模、计算精度和时效性的要求。  相似文献   

9.
Decision‐making in reservoir operation has become easy and understandable with the use of fuzzy logic models, which represent the knowledge in terms of interpretable linguistic rules. However, the improvement in interpretability with increase in number of fuzzy sets (‘low’, ‘high’, etc) comes with the disadvantage of increase in number of rules that are difficult to comprehend by decision makers. In this study, a clustering‐based novel approach is suggested to provide the operators with a limited number of most meaningful operating rules. A single triangular fuzzy set is adopted for different variables in each cluster, which are fine‐tuned with genetic algorithm (GA) to meet the desired objective. The results are compared with the multi fuzzy set fuzzy logic model through a case study in the Pilavakkal reservoir system in Tamilnadu State, India. The results obtained are highly encouraging with a smaller set of rules representing the actual fuzzy logic system. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

10.
ABSTRACT

Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability.  相似文献   

11.
 We illustrate a method of global sensitivity analysis and we test it on a preliminary case study in the field of environmental assessment to quantify uncertainty importance in poorly-known model parameters and spatially referenced input data. The focus of the paper is to show how the methodology provides guidance to improve the quality of environmental assessment practices and decision support systems employed in environmental policy. Global sensitivity analysis, coupled with uncertainty analysis, is a tool to assess the robustness of decisions, to understand whether the current state of knowledge on input data and parametric uncertainties is sufficient to enable a decision to be taken. The methodology is applied to a preliminary case study, which is based on a numerical model that employs GIS-based soil data and expert consultation to evaluate an index that joins environmental and economic aspects of land depletion. The index is used as a yardstick by decision-makers involved in the planning of highways to identify the route that minimises the overall impact.  相似文献   

12.
The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO2 input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

13.
Annual and monthly streamflows for 729 rivers from a global data set are used to assess the adequacy of five techniques to estimate the relationship between reservoir capacity, target draft (or yield) and reliability of supply. The techniques examined are extended deficit analysis (EDA), behaviour analysis, sequent peak algorithm (SPA), Vogel and Stedinger empirical (lognormal) method and Phien empirical (Gamma) method. In addition, a technique to adjust SPA using annual flows to account for within-year variations is assessed. Of our nine conclusions the key ones are, firstly, EDA is a useful procedure to estimate streamflow deficits and, hence, reservoir capacity for a given reliability of supply. Secondly, the behaviour method is suitable to estimate storage but has limitations if an annual time step is adopted. Thirdly, in contrast to EDA and behaviour which are based on time series of flows, if only annual statistics are available, the Vogel and Stedinger empirical method compares favorably with more detailed simulation approaches.  相似文献   

14.
While spatial autocorrelation is used in spatial sampling survey to improve the precision of the feature’s estimate of a certain population at area units, spatial heterogeneity as the stratification frame in survey also often have a considerable effect upon the precision. Under the context of increasingly enriched spatiotemporal data, this paper suggests an information-fusion method to identify pattern of spatial heterogeneity, which can be used as an informative stratification for improving the estimation accuracy. Data mining is major analysis components in our method: multivariate statistics, association analysis, decision tree and rough set are used in data filter, identification of contributing factors, and examination of relationship; classification and clustering are used to identify pattern of spatial heterogeneity using the auxiliary variables relevant to the goal and thus to stratify the samples. These methods are illustrated and examined in the case study of the cultivable land survey in Shandong Province in China. Different from many stratification schemes which just uses the goal variable to stratify which is too simplified, information from multiple sources can be fused to identify pattern of spatial heterogeneity, thus stratifying samples at geographical units as an informative polygon map, and thereby to increase the precision of estimates in sampling survey, as demonstrated in our case research.  相似文献   

15.
This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes.  相似文献   

16.
《Marine pollution bulletin》2014,83(1-2):194-200
Concentrations of heavy metals in river water and sediment were investigated in nine estuaries along the coast of Bohai Bay, Northern China. Multivariate statistical techniques such as principal component analysis and cluster analysis, in combination with metal concentration analysis and correlation analysis, were used to identify the possible sources of the metals and the pollution pattern in nine estuaries along the coast of Bohai Bay. The environmental risks of metals, evaluated by sediment quality guidelines and background values, revealed Hg contamination in the estuaries. However, levels of Cd in estuarine sediments were low, and they were less than those levels in river sediments, partly due to the high mobility and dilution of river or seawater. Cd did not contribute to sediment deposits in estuaries. High organic matter from effluents from large municipal sewage treatment plants was predominantly responsible for restricting Hg mobility from the river to Bohai Bay.  相似文献   

17.
In this study, a multistage scenario-based interval-stochastic programming (MSISP) method is developed for water-resources allocation under uncertainty. MSISP improves upon the existing multistage optimization methods with advantages in uncertainty reflection, dynamics facilitation, and risk analysis. It can directly handle uncertainties presented as both interval numbers and probability distributions, and can support the assessment of the reliability of satisfying (or the risk of violating) system constraints within a multistage context. It can also reflect the dynamics of system uncertainties and decision processes under a representative set of scenarios. The developed MSISP method is then applied to a case of water resources management planning within a multi-reservoir system associated with joint probabilities. A range of violation levels for capacity and environment constraints are analyzed under uncertainty. Solutions associated different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help water managers to identify desired policies under various economic, environmental and system-reliability conditions. Besides, sensitivity analyses demonstrate that the violation of the environmental constraint has a significant effect on the system benefit.  相似文献   

18.
C. Dobler  F. Pappenberger 《水文研究》2013,27(26):3922-3940
The increasing complexity of hydrological models results in a large number of parameters to be estimated. In order to better understand how these complex models work, efficient screening methods are required in order to identify the most important parameters. This is of particular importance for models that are used within an operational real‐time forecasting chain such as HQsim. The objectives of this investigation are to (i) identify the most sensitive parameters of the complex HQsim model applied in the Alpine Lech catchment and (ii) compare model parameter sensitivity rankings attained from three global sensitivity analysis techniques. The techniques presented are the (i) regional sensitivity analysis, (ii) Morris analysis and (iii) state‐dependent parameter modelling. The results indicate that parameters affecting snow melt as well as processes in the unsaturated soil zone reveal high significance in the analysed catchment. The snow melt parameters show clear temporal patterns in the sensitivity whereas most of the parameters affecting processes in the unsaturated soil zone do not vary in importance across the year. Overall, the maximum degree day factor (meltfunc_max) has been identified to play a key role within the HQsim model. Although the parameter sensitivity rankings are equivalent between methods for a number of parameters, for several key parameters differing results were obtained. An uncertainty analysis demonstrates that a parameter ranking attained from only one method is subjected to large uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

19.
In risk assessment studies it is important to determine how uncertain and imprecise knowledge should be included into the simulation and assessment models. Thus, proper evaluation of uncertainties has become a major concern in environmental and health risk assessment studies. Previously, researchers have used probability theory, more commonly Monte Carlo analysis, to incorporate uncertainty analysis in health risk assessment studies. However, in conducting probabilistic health risk assessment, risk analyst often suffers from lack of data or the presence of imperfect or incomplete knowledge about the process modeled and also the process parameters. Fuzzy set theory is a tool that has been used in propagating imperfect and incomplete information in health risk assessment studies. Such analysis result in fuzzy risks which are associated with membership functions. Since possibilistic health risk assessment studies are relatively new, standard procedures for decision-making about the acceptability of the resulting fuzzy risk with respect to a crisp standard set by the regulatory agency are not fully established. In this paper, we are providing a review of several available approaches which may be used in decision-making. These approaches involve defuzzification techniques, the possibility and the necessity measures. In this study, we also propose a new measure, the risk tolerance measure, which can be used in decision making. The risk tolerance measure provides an effective metric for evaluating the acceptability of a fuzzy risk with respect to a crisp compliance criterion. Fuzzy risks with different membership functions are evaluated with respect to a crisp compliance criterion by using the possibility, the necessity, and the risk tolerance measures and the results are discussed comparatively.  相似文献   

20.
Regression-based methods are commonly used for riverine constituent concentration/flux estimation, which is essential for guiding water quality protection practices and environmental decision making. This paper developed a multivariate adaptive regression splines model for estimating riverine constituent concentrations (MARS-EC). The process, interpretability and flexibility of the MARS-EC modelling approach, was demonstrated for total nitrogen in the Patuxent River, a major river input to Chesapeake Bay. Model accuracy and uncertainty of the MARS-EC approach was further analysed using nitrate plus nitrite datasets from eight tributary rivers to Chesapeake Bay. Results showed that the MARS-EC approach integrated the advantages of both parametric and nonparametric regression methods, and model accuracy was demonstrated to be superior to the traditionally used ESTIMATOR model. MARS-EC is flexible and allows consideration of auxiliary variables; the variables and interactions can be selected automatically. MARS-EC does not constrain concentration-predictor curves to be constant but rather is able to identify shifts in these curves from mathematical expressions and visual graphics. The MARS-EC approach provides an effective and complementary tool along with existing approaches for estimating riverine constituent concentrations.  相似文献   

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