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1.
Risk-based decision-making for drilling waste discharges using a fuzzy synthetic evaluation technique 总被引:5,自引:0,他引: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
2.
Gyan?Chhipi-ShresthaEmail author Julie?Mori Kasun?Hewage Rehan?Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(2):417-430
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
3.
Amir?NafiEmail author Eric?Crastes Rehan?Sadiq Denis?Gilbert Olivier?Piller 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):527-544
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
4.
Bingyi Kang Gyan Chhipi-Shrestha Yong Deng Kasun Hewage Rehan Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1743-1758
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
5.
E. Aghaarabi F. Aminravan R. Sadiq M. Hoorfar M. J. Rodriguez H. Najjaran 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(3):655-679
This paper presents the use of two multi-criteria decision-making (MCDM) frameworks based on hierarchical fuzzy inference engines for the purpose of assessing drinking water quality in distribution networks. Incommensurable and uncertain water quality parameters (WQPs) at various sampling locations of the water distribution network (WDN) are monitored. Two classes of WQPs including microbial and physicochemical parameters are considered. Partial, incomplete and subjective information on WQPs introduce uncertainty to the water quality assessment process. Likewise, conflicting WQPs result in a partially reliable assessment of the quality associated with drinking water. The proposed methodology is based on two hierarchical inference engines tuned using historical data on WQPs in the WDN and expert knowledge. Each inference engine acts as a decision-making agent specialized in assessing one aspect of quality associated with drinking water. The MCDM frameworks were developed to assess the microbial and physicochemical aspects of water quality assessment. The MCDM frameworks are based on either fuzzy evidential or fuzzy rule-based inference. Both frameworks can interpret and communicate the relative quality associated with drinking water, while the second is superior in capturing the nonlinear relationships between the WQPs and estimated water quality. More comprehensive rules will have to be generated prior to reliable water quality assessment in real-case situations. The examples presented here serve to demonstrate the proposed frameworks. Both frameworks were tested through historical data available for a WDN, and a comparison was made based on their performance in assessing levels of water quality at various sampling locations of the network. 相似文献
6.
Jie Liu Yunpeng Li Rehan Sadiq Yong Deng 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(6):1323-1331
Many researches have been conducted on the health influence of Particle Matter with diameters less than 2.5 microns (PM \(_{2.5}\) ). There are also some researches on the cause of PM \(_{2.5}\) . However, such research generally focuses on the economic and political aspect of the environment issue. In this paper, a data-analysis approach of the PM \(_{2.5}\) issue is raised to offer a new viewpoint of this problem. The applied method extracts the relations of air quality system record as a relation map, which illustrates the influence among the parameters in a graph. The method successfully fitted the weather record, and derived from it the influencers of PM \(_{2.5}\) . The result shows that the average temperature, average barometric pressure and concentration of Ozone are all factors that have an influence on the concentration of PM \(_{2.5}.\) A short justification of it is also provided. 相似文献
7.
Jewgenij Torizin Michael Fuchs Adnan Alam Awan Ijaz Ahmad Sardar Saeed Akhtar Simon Sadiq Asif Razzak Daniel Weggenmann Faseeh Fawad Nimra Khalid Faisan Sabir Ahsan Jamal Khan 《Natural Hazards》2017,87(2):757-771
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
8.
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
9.
David McEntire Jill Souza Matthew Lloyd Collins Ekong J. Peters Abdul-Akeem Sadiq 《Natural Hazards》2012,61(3):1389-1409
This paper underscores the importance of damage assessment and recognizes the direct effect it has on post-disaster response
and recovery operations. The paper first explores the literature on this subject, including the history, types, methods, and
problems relating to damage assessment. After discussing the employed research methodology, the paper uses the Paso Robles
(San Simeon, California) earthquake as a case study to illustrate the challenges and successes with regard to damage assessment.
Logistics, politics, information management, coordination, preparedness, and other topics are discussed in this section. The
paper concludes with lessons and opportunities for research and its application. 相似文献
10.
Rehan Sadiq Solomon Tesfamariam 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(4):495-505
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