Probabilistic risk analysis using ordered weighted averaging (OWA) operators

The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complexities increase further when the empirical relationships are not strong enough to derive physical-based models. In this paper, ordered weighted averaging (OWA) operators are proposed to estimate the system load. The risk of failure is estimated by assuming normally distributed reliability index. The proposed methodology for risk analysis is illustrated using an example of nine-input parameters. Sensitivity analyses identified that the risk of failure is dominated by the attitude of a decision-maker to generate OWA weights, missing input parameters and system capacity.

Mineral potential mapping in Central Iran using fuzzy ordered weighted averaging method

The aim of this work is to introduce the application of the fuzzy ordered weighted averaging method as a straightforward knowledge‐driven approach to explore porphyry copper deposits in an airborne prospect. In this paper, the proposed method is applied to airborne geophysical (potassium radiometry, magnetometry, and frequency‐domain electromagnetic) data, geological layers (fault and host rock zones), and various extracted alteration layers from remote sensing images. The central Iranian volcanic–sedimentary belt in Kerman province of Iran that is located within the Urumieh–Dokhtar (Sahand–Bazman) magmatic arc is chosen for this study. This region has high potential of mineral occurrences, especially porphyry copper, containing some active world‐class copper mines such as Sarcheshmeh. Two evidential layers, including the downward continued map and the analytic signal of such filtered magnetic data, are generated to be used as geophysical plausible traces of porphyry copper occurrences. The low values of the resistivity layer acquired from airborne frequency‐domain electromagnetic data are also used as an electrical criterion in this study. Four remote sensing evidential layers, including argillic, phyllic, propylitic, and hydroxyl alterations, are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer images in order to map the altered areas associated with porphyry copper deposits. The Enhanced Thematic Mapper plus images are used to map iron oxide layer. Since potassium alteration is the mainstay of copper alteration, the airborne potassium radiometry data are used. Here, the fuzzy ordered weighted averaging method uses a wide range of decision strategies in order to generate numerous mineral potential/prospectivity maps. The final mineral potential map based upon desired geo‐data set indicates adequately matching of high‐potential zones with previous working mines and copper deposits.     

Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP)

Environmental risk management is an integral part of risk analyses. The selection of different mitigating or preventive alternatives often involve competing and conflicting criteria, which requires sophisticated multi-criteria decision-making (MCDM) methods. Analytic hierarchy process (AHP) is one of the most commonly used MCDM methods, which integrates subjective and personal preferences in performing analyses. AHP works on a premise that decision-making of complex problems can be handled by structuring the complex problem into a simple and comprehensible hierarchical structure. However, AHP involves human subjectivity, which introduces vagueness type uncertainty and necessitates the use of decision-making under uncertainty. In this paper, vagueness type uncertainty is considered using fuzzy-based techniques. The traditional AHP is modified to fuzzy AHP using fuzzy arithmetic operations. The concept of risk attitude and associated confidence of a decision maker on the estimates of pairwise comparisons are also discussed. The methodology of the proposed technique is built on a hypothetical example and its efficacy is demonstrated through an application dealing with the selection of drilling fluid/mud for offshore oil and gas operations.