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Mamdani fuzzy inference system has been widely used for potential risk modelling and management. The decision-making is usually provided by multiple experts in the field. The conflicting information in sources from different experts become an open issue and has attracted some researchers to investigate further. Various risk factors in a project caused difficulties for decision makers to make reliable decisions on the whole project since it involves ambiguities, vagueness, and fuzziness. The introduction of the fuzzy inference system to the evaluation of construction risk is capable in explaining its reasoning process and, hence, overcoming such problems. Risk factors under the project management risk were identified through literature sources and from the opinion of experts. It is found that the likelihood and severity of risk is somehow interlinked with the concept of fuzzy theory. For model input and output linguistics variables, the triangular membership function was selected. The methodology employs a fuzzy aggregation system in which an appropriate control action can be determined by the acquisition of expert judgment. A total of 23 rules with logical OR operator, truncation implication, and Mean of Maxima (MoM) method for defuzzification were used to create an effective fuzzy model intended for making decisions. The framework determines the relationship between input and output parameters in if-then rules or mathematical functions using an effective fuzzy arithmetic operator. The study addresses the principle issues of multiexpert opinions based on Mamdani-type decision system and the illustrative example taken from one of medium-sized project held in Malaysia's construction industry. By comparing with other experimental results, we verify the rationality and reliability of the proposed method. [ABSTRACT FROM AUTHOR]

Mamdani fuzzy inference system has been widely used for potential risk modelling and management. The decision-making is usually provided by multiple experts in the field. The conflicting information in sources from different experts become an open issue and has attracted some researchers to investigate further. Various risk factors in a project caused difficulties for decision makers to make reliable decisions on the whole project since it involves ambiguities, vagueness, and fuzziness. The introduction of the fuzzy inference system to the evaluation of construction risk is capable in explaining its reasoning process and, hence, overcoming such problems. Risk factors under the project management risk were identified through literature sources and from the opinion of experts. It is found that the likelihood and severity of risk is somehow interlinked with the concept of fuzzy theory. For model input and output linguistics variables, the triangular membership function was selected. The methodology employs a fuzzy aggregation system in which an appropriate control action can be determined by the acquisition of expert judgment. A total of 23 rules with logical OR operator, truncation implication, and Mean of Maxima (MoM) method for defuzzification were used to create an effective fuzzy model intended for making decisions. The framework determines the relationship between input and output parameters in if-then rules or mathematical functions using an effective fuzzy arithmetic operator. The study addresses the principle issues of multiexpert opinions based on Mamdani-type decision system and the illustrative example taken from one of medium-sized project held in Malaysia's construction industry. By comparing with other experimental results, we verify the rationality and reliability of the proposed method. [ABSTRACT FROM AUTHOR]

The objective of this study is to use the Bayesian quantile regression for studying the retirement consumption puzzle, which is defined as the drop in consumption upon retirement, using the cross-sectional data of the Malaysian Household Expenditure Survey (HES) 2009/2010. Three different measures of consumption, namely, total expenditure, work-related expenditure, and nonwork-related expenditure, are suggested for studying the retirement consumption puzzle. The results show that the drop in consumption upon retirement is significant and has a regressive distributional effect as indicated by larger drops at lower percentiles and smaller drops at higher percentiles. The smaller drops among higher consumption retirees (or higher income retirees) may imply that they have more savings and/or retirement benefits than the smaller consumption retirees (or lower income retirees). Comparison between the three types of consumption shows that the work-related expenditure has a uniform drop across the distribution. The drop under the nonwork-related expenditure varies across the distribution, implying that it is the source behind the variation of the consumption drop. [ABSTRACT FROM AUTHOR]

The particles trapped in the Earth's inner radiation belts could harm low Earth orbit (LEO) satellites. Although the inner radiation belts are usually stable, their response to extremely large solar geomagnetic events can produce satellite anomalies. The risk is higher because of frequent LEO satellite passes through the South Atlantic Anomaly (SAA). A model for forecasting the trapped particle flux distribution in equatorial LEO based on the hierarchical Bayesian spatio-temporal (HBST) statistical model was developed to address the risk to satellites. This model is applicable to low- and mediumenergy electrons and protons under all solar activity conditions. Dynamic rather than static data were also used. A simple HBST model named the Gaussian process (GP) was developed using NOAA 15-17 data, which categorized particle energies as > 30 keV (mepOel) and > 300 keV (mep0e3) for electrons and 80 - 240 keV (mep0p2) and 800 - 2500 keV (mep0p4) for protons in the SAA region. The goal of this study is to examine the applicability of this model during a quiet period (15-19 May 2009) and a period of high solar activity (26 - 30 October 2003). The forecast was then interpolated using a Kriging technique to estimate the particle distribution. Statistical and visual validations showed good indicators, with average mean relative error (MRE) values of 20 - 30% for both periods and a similar pattern as that of the National Oceanic and Atmospheric Administration (NOAA) map. This work contributes a method for predicting the trapped particle flux distribution at low latitude LEOs. [ABSTRACT FROM AUTHOR]