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1.
Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors.  相似文献   
2.
Clostridium difficile infection is one of the major patient safety concerns in hospitals worldwide. Clostridium difficile infection can have high economic burden to patients, hospitals, and government. Limited work has been done in the area of predictive modeling. In this article, A new predictive model based on Gaussian mixture model and Dempster–Shafter theory is proposed to predict Clostridium difficile infection incidence in hospitals. First, the Gaussian mixture model and expectation–maximization algorithms are used to generate explicit probability criteria of risk factors based on the given data. Second, Dempster–Shafter theory is used to predict the Clostridium difficile infection incidence based on the generated probability criteria that have different beliefs attributing to their different credits. The main procedure includes (1) generate the probability criteria model using Gaussian mixture model and expectation–maximization algorithm; (2) determine the credit of the probability criteria; (3) generate the basic probability assignment; (4) discount the evidences; (5) aggregate the evidences using Dempster combining rule; (6) predict Clostridium difficile infection incidence using pignistic probability transformation. Results show that the model has a higher accuracy than an existing model. The proposed model can generate the criteria ratings of risk factors automatically, which would potentially prevent the imprecision caused by the subjective judgement of experts. The proposed model can assist risk managers and hospital administrators in the prediction and control of Clostridium difficile infection incidence with optimizing their resources.  相似文献   
3.
Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (HyetosCat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled HyetosCat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
4.
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   
5.
Offshore petroleum drilling wastes contain toxic substances that are potentially harmful to the marine ecosystem. Despite environmentally benign characteristics, wastes associated with synthetic-based fluids still contain a certain amount of pollutants due to contamination with formation oil and the presence of trace heavy metals in barite, which may pose risk when discharged into the marine environment. A framework is presented here for a decision support system for the selection of the best drilling waste discharge option. Uncertainties in the quantification of risk, cost and technical feasibility are expressed by fuzzy numbers. An analytical hierarchy process with a technique called fuzzy synthetic evaluation is employed to determine the best management alternative (discharge scenario).  相似文献   
6.
Economic damage assessment for flood risk estimation is established in many countries, but attentions have been focused on macro- or meso-scale approaches and less on micro-scale approaches. Whilst the macro- or meso-scale approaches of flood damage assessment are suitable for regional- or national-oriented studies, micro-scale approaches are more suitable for cost–benefit analysis of engineered protection measures. Furthermore, there remains lack of systematic and automated approaches to estimate economic flood damage for multiple flood scenarios for the purpose of flood risk assessment. Studies on flood risk have also been driven by the assumption of stationary characteristic of flood hazard, hence the stationary-oriented vulnerability assessment. This study proposes a novel approach to assess vulnerability and flood risk and accounts for adaptability of the approach to nonstationary conditions of flood hazard. The approach is innovative in which an automated concurrent estimation of economic flood damage for a range of flood events on the basis of a micro-scale flood risk assessment is made possible. It accounts for the heterogeneous distribution of residential buildings of a community exposed to flood hazard. The feasibility of the methodology was tested using real historical flow records and spatial information of Teddington, London. Vulnerability curves and residual risk associated with a number of alternative extents of property-level protection adoptions are estimated by the application of the proposed methodology. It is found that the methodology has the capacity to provide valuable information on vulnerability and flood risk that can be integrated in a practical decision-making process for a reliable cost–benefit analysis of flood risk reduction options.  相似文献   
7.
Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (ASCE J Environ Eng 126(5):451–455, 2000) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and sensitivity of the proposed approach.  相似文献   
8.
Analytic hierarchy process (AHP) is a utility theory based decision-making technique, which works on a premise that the decision-making of complex problems can be handled by structuring them into simple and comprehensible hierarchical structures. However, AHP involves human subjective evaluation, which introduces vagueness that necessitates the use of decision-making under uncertainty. The vagueness is commonly handled through fuzzy sets theory, by assigning degree of membership. But, the environmental decision-making problem becomes more involved if there is an uncertainty in assigning the membership function (or degree of belief) to fuzzy pairwise comparisons, which is referred to as ambiguity (non-specificity). In this paper, the concept of intuitionistic fuzzy set is applied to AHP, called IF-AHP to handle both vagueness and ambiguity related uncertainties in the environmental decision-making process. The proposed IF-AHP methodology is demonstrated with an illustrative example to select best drilling fluid (mud) for drilling operations under multiple environmental criteria.  相似文献   
9.
This paper presents laboratory experiments and numerical simulations of effects of submerged obstacles on tsunami-like solitary wave and its run-up. This study was carried out for the breaking and non-breaking solitary waves on 1:19.85 uniform slope which contains a submerged obstacle. New laboratory experiments are performed to describe the mitigation of tsunami amplitude and run-up under the effect of submerged obstacles. We are based on experimental results obtained to validate the numerical model. The numerical modeling using COULWAVE aims essentially to show the effect of the obstacle on the shape of solitary wave and the limit of this effect. Using a multiple nonlinear regression, we have determined a model to estimate height of run-up according to the amplitude of the wave and the obstacle peak depth.  相似文献   
10.
Abstract

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST's distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing via three feedback mechanisms; and (3) representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs). The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture. Furthermore, the representation of soil moisture variability and routing processes at the sub-grid scale enables the CREST model to be readily scalable to multi-scale modelling research. This paper presents the model development and demonstrates its applicability for a case study in the Nzoia basin located in Lake Victoria, Africa.

Citation Wang, J., Yang, H., Li, L., Gourley, J. J., Sadiq, I. K., Yilmaz, K. K., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., Limaye, A. S., Korme, T. &; Okello, L. (2011) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol. Sci. J. 56(1), 84–98.  相似文献   
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