城市地震灾害风险评价的数学模型

本文用模糊集方法建立了城市地震灾害风险评价的数学模型，是文献［１，２］所述风险模型在地震灾害分析中的具体应用。本文详细介绍了如何确定模糊超越率μｚ（ｙ，ｘ）的途径，并提供了计算承灾体灾害程度可能性分布ＰＯＳＳ（ｌ，ｙ）的方法。     

灾害损失等级划分的模糊灾度判别法

作者应用模糊模式识别理论于灾害损失等级划分的研究，提出了模糊灾度概念，并建立了模糊灾度等级的隶属函数，从而给出了一种可用于灾害损失等级划分的模糊灾度判别法。     

Development of a scale for assessing the organization's safety performance based fuzzy ANP

Traditionally, safety performance is assessed through statistical analyses of incident data, known as lagging indicators. Lagging indicators are not useful since the goal of founding safety management systems is the continuous improvement. In this study, a scale was established and validated to assess the elements that affect the organization safety. The fuzzy analytic network process (FANP) procedure was applied to weigh the elements and to reveal the influence of various structures for the proposed scales on the safety performance indicator. A 120-item scale was developed following the interview process to examine the factors that affect safety performance. Based on the face validity results, eight items were removed. The mean value of the instrument's validity index was 0.79. According to the FANP results, the organizational factor had the highest weight load of 0.465, whereas the environmental factor, with a weight of 0.209, had the least effect on the organization's safety performance index. An analysis of the study data showed that the designed scale can be used as an objective and simple tool to evaluate the factors that affect safety performance.     

A unique intelligent approach for forecasting project completion time in oil refineries

This study presents a hybrid approach for accurate forecasting of project completion time with noisy and uncertain safety factors in oil refineries. The hybrid approach is based on artificial neural network (ANN), fuzzy mathematical programming (FMP) and conventional regression. Three indictors, namely, number of occupational injuries, number of employees and ratio of maximum useful hours over useful hour per month are considered as inputs. Also, project completion time is considered as the main output. To achieve the objective of this study, five sets of data with respect to oil refinery construction projects in various cities of Iran are collected and analyzed through statistical methods. It is shown that for the actual case of this study, ANN presents lowest mean absolute percentage error (MAPE). Also, analysis of variance (ANOVA) is used to verify and validate the results of this study. This is the first study that presents a hybrid approach for accurate estimation and forecasting of project completion time with complex, noisy and uncertain occupational factors.     

Assessing livelihood for improvement: Samanalawewa reservoir environs,Sri Lanka

This paper explores household (HH)-level livelihood dynamics and determinants since construction of the Samanalawewa Hydroelectricity Reservoir (SHER) in the Samanalawewa watershed, Sri Lanka. The research is based on data from a structured questionnaire survey of 201 randomly selected households (HHs) in upstream and downstream areas. Livelihood dynamics at two separate points in time (1988 and 2008) were assessed based on a sustainable livelihood framework (SLF). Impact of livelihood determinants on livelihood was analysed using factor and regression analysis techniques, followed by an optimisation procedure to suggest requirements in selected significant determinants to improve the livelihood of various categories of farm HH. In both upstream and downstream areas, livelihood assets, viz. physical, social and human capital, increased significantly, while access to natural and financial capital decreased significantly and slightly, respectively, during last two decades. The factor analysis extracted six factors in the upstream area and seven in the downstream area. The derived regression models show that nine variables in the upstream area and ten in the downstream area are major determinants of HH livelihood. Based on optimisation results, policy implications are discussed in relation to needed improvements in livelihood determinants to improve overall livelihood of HHs.     

Ports’ service attributes for ship navigation safety

The purpose of this paper is to discuss the service attributes of ports for ship navigation safety. Based on the relevant literature and the features of ship navigation in ports, the service attributes of ports for ship navigation were first investigated. A fuzzy AHP model was then used to identify those attributes from shipmasters’ perspectives. Finally, a Dissatisfaction Attitude (DA) index was used to determine the attributes’ priorities, by which the port authorities may make policies for improving ship navigation safety. As an empirical study, the shipmasters berthing their ships in Kaohsiung Port were surveyed to validate the model. The result constructs 19 port service attributes (SAs) for ship navigation safety, in which, the shipmasters place more emphasis on the SAs of operators’ professional literacy, including the marine pilot’s professional and English communication abilities, the VTC (Vessel Traffic Center) regulator’s professional and English communication abilities, and the tugboat driver’s skills. While, for Kaohsiung Port, currently, the traffic control of fairway is the most important aspect to be improved. The theoretical and managerial implications of the findings for port authorities in improving ship navigation safety are discussed.     

Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects

Selection problems are common in process engineering. In most cases, it is necessary to rank alternatives based on multiple criteria (e.g., cost, safety, environmental impact), which are often conflicting. In addition, some criteria may be fundamentally difficult to quantify due to data scarcity, in which case subjective assessments need to be used as a proxy. Decision analysis tools such as the analytic hierarchy process (AHP) are useful to ensure decision-making is done rationally. In this work, we propose a fuzzy AHP variant, wherein pairwise comparison of decision elements by domain experts is expressed with triangular fuzzy numbers. This approach allows the degree of confidence of the expert to be quantified explicitly; it also allows inconsistencies in judgment to be reconciled within the bounds of the fuzzy numbers to generate reasonable values for the weighting factors. We demonstrate the methodology on three case studies, involving the comparison of different types of chlor-alkali electrolytic cells, CO₂ capture techniques in cement plants and wastewater treatment options for municipal wastewater.     

Fuzzy risk modeling of process operations in the oil and gas refineries

Operating several assets has resulted in more complexity and so occurrence of some major accidents in the refining industries. The process operations risk factors including failure frequency and the consequence components like employees' safety and environment impacts, operation downtime, direct and indirect cost of operations and maintenance, and mean time to repair should be considered in the analysis of these major accidents in any refinery. Considering all of these factors, the risk based maintenance (RBM) as a proper risk assessment methodology minimizes the risk resulting from asset failures. But, one of the main engineering problems in risk modeling of the complex industries like refineries is uncertainty due to the lack of information. This paper proposes a model for the risk of the process operations in the oil and gas refineries. The fuzzy logic system (FLS) was proposed for risk modeling. The merit of using fuzzy model is to overcome the uncertainty of the RBM components. This approach also can be accounted as a benchmark for future failures. A unified risk number would be obtained to show how the criticality of units is. The case study of a gas plant in an oil refinery is performed to illustrate the application of the proposed model and a comparison between the results of both traditional RBM and fuzzy method is made.For the case study, 26 asset failures were identified. The fuzzy risk results show that 3 failures have semi-critical level and other 23 failures are non-critical. In both traditional and fuzzy RBM methods, some condenser failures had the highest risk number and some pumps were prioritized to have the lowest risk level. The unit with unified risk number less than 40 is in the non-critical conditions. Proposed methodology is also applicable to other industries dealing with process operations risks.     

加油站模糊数学安全评价模型及应用

笔者针对目前汽车加油站事故的多发性及其安全的重要性 ,指出了目前加油站安全评价方法的不足 ,提出对于加油站这个复杂的多因素、多变量、多层次人机系统应该考虑采用模糊数学的方法来进行安全评价 ,以得到符合实际加油站安全现状的评价结果。通过分析影响加油站安全的各个因素以及因素之间的相互联系 ,建立了较合理的加油站安全评价指标体系 ;并根据现场经验给出了各相关安全因素的权重 ,运用模糊数学方法建立了加油站安全评价模型 ;同时通过实例验证 ,该安全评价模型的评价结果符合实际情况 ,有较强的实际应用性     

平煤集团煤与瓦斯突出强度预测的模糊综合评判

依据平煤集团历年煤与瓦斯突出事例的统计数据,应用7±2心理极限概念,合理选定模糊评判因素集,采用层次分析法确定各因素对突出强度的贡献度权重;采用定性数据定量化理论建立了各因素隶属于大型突出、中型突出和小型突出的隶属度;采用二级模糊综合评判方法和“加权平均型”评判数学模型,在国内外首次建立了煤与瓦斯突出强度预测模糊综合评判方法,按最大隶属度判别准则实现对突出强度的定量预测。对平煤集团91次突出事例突出强度预测验证表明,验证正确率为94 .5 % ,说明提出的煤与瓦斯突出强度预测方法在技术上是可行的,对突出矿井煤与瓦斯突出预测具有重要的指导意义。