住宅小区绿色生态性评价研究

通过构建住宅小区绿色生态性评价指标体系,综合运用层次分析法和模糊数学理论等系统工程理论和方法,系统评价了住宅小区的绿色生态性,为其研究提供新的途径。     

A framework for resilience assessment in process systems using a fuzzy hybrid MCDM model

Resilience engineering (RE) has recently emerged as a novel safety management paradigm in socio-technical organizations. It is believed that RE is more compatible with the characteristics of complex socio-technical systems. The multicriteria nature and the presence of both qualitative and quantitative latent factors make RE substantially more complex especially in quantifying and modeling aspects. To address this issue, the present research aims to develop a fuzzy hybrid multicriteria decision-making (MCDM) model for quantifying and evaluating resilience using the fuzzy Analytic hierarchy process (F-AHP) and fuzzy VIKOR (F-VIKOR) techniques. Initially, an evaluation framework including six resilience indicators and 43 sub-indicators was established. Afterward, the F-AHP method was used to determine the weight of the resilience indicators, while the F-VIKOR method was employed to rank the resilience performance of the different operational units. To present the model capability, we evaluated the resilience of a gas refinery as a typical instance of socio-technical systems. The findings revealed the performance level of resilience indicators in all units of the studied refinery and their ranking based on the computation of the index value (Qi). With respect to the Qi values, the best and worst performance of units from the resilience perspective was specified. Results indicate that the proposed model can serve as an effective evaluation approach in complicated systems and can be used to effectively design strategies to improve system safety performance. To the best of our knowledge, this is the first study that evaluates the resilience using the VIKOR and AHP in a fuzzy environment in the process industry.     

Risk assessment of coupling links in hazardous chemicals maritime transportation system

The hazardous chemicals maritime transportation system (HCMTS) belongs to a typical complex tech-social system, which is comprised of multiple functions with interactions. To quantitatively assess the risks triggered by failure coupling links (CLs) between upstream and downstream functions, a hybrid method integrating the Functional Resonance Analysis Method (FRAM), fuzzy set theory, and risk matrix is proposed in the present study. A total of 10 essential functions and 16 CLs involved in HCMTS were identified by FRAM. The fuzzy set theory was adopted to aggregate the weights of risk consequence and likelihood for CLs. A risk matrix with a continuous scale was utilized to assess and rank the CLs’ risks. The results have been demonstrated by the comparisons, indicated that the risk indexes (RIs) of the CLs between the functions < Consignment of HCs> and <Undertaking the transportation>, <Consignment of HCs> and <Declaration of HCs>, <Loading HCs in port> and <Ship navigation at sea > are higher in the whole chain of HCMTS.     

大连市生态环境质量研究

运用可持续发展理论和生态经济学原理,从白然、社会、经济的角度,选取了20个单项指标,构建了大连生态环境质量评价指标体系,采用专家打分法、层次分析法和模糊综合评判法构建出城市生态环境质量评价的模型,定量地对大连的生态环境进行了综合评价。     

基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*

为分析海底管道运行中存在的泄漏风险,提出1种基于毕达哥拉斯模糊数与贝叶斯网络的风险评估模型。首先,通过毕达哥拉斯模糊数转换专家定性评价,拓展专家意见模糊范围;然后,结合主客观组合赋权法,利用毕达哥拉斯梯形爱因斯坦混合几何算子（PTFEHG）实现专家意见的聚合;最后,通过贝叶斯网络的推理与敏感性分析,计算海底管道泄漏风险的失效概率,并辨识关键风险因素。研究结果表明:该方法可以结合专家意见对海底管道泄漏风险进行定量分析,并识别导致泄漏事故的关键风险因素,对海底管道安全管理具有指导意义。     

煤矿井下瓦斯突出危险性的模糊分析

基于模糊可能性理论建立了瓦斯突出危险性函数。应用模糊多元分析方法建立了瓦斯突出危险性分析模型,通过对各类确定与非确定信息的模糊综合分析,预测煤矿开采过程中瓦斯突出的危险性,并在生产中应用该模型取得了较好的效果。     

泥石流危险等级评价的模糊数学方法

本文在文献[1]泥石流危险度研究的基础上.提出泥石流危险性评价的模糊数学方法。文中首先根据有关资料建立了评定因子的隶属函数以及各因子在评定泥石流危险性中权重的模糊子集,并在此基础上运用模糊综合评判技术提出了确定泥石流危险等级模糊向量的方法。     

A fuzzy risk assessment approach for occupational hazards in the construction industry

The techniques in the construction industry have been improved due to the rapid development of science and technology. However, the constructional hazards are not decreased as expected. To reduce or prevent occupational hazards in the construction industry, a fuzzy risk assessment method was proposed to provide a prevention and improvement technique against occupational hazards. This method used two-stage quality function deployment (QFD) tables to represent the relationships among construction items, hazard types and hazard causes. A fuzzy analytic network process (ANP) method was developed to identify important hazard types and hazard causes. Failure modes and effect analysis (FMEA) was performed to assess the risk value of hazard causes based on the fuzzy inference approach. The proposed method was applied to a telecom engineering company in southern Taiwan. The performance evaluation result indicated that this method can provide satisfactory risk assessment values of hazard causes and relevant improvement strategies.     

Accident data for the Semantic Web

This paper describes concerns about the documentation, dissemination and use of lessons learned from mishap investigations, impediments posed by current practices, and opportunities for improvement. Lessons are presently developed, documented and stored primarily in narrative form and relational databases, and disseminated in many forms and media, including the Internet. Current practices pose many impediments to maximized development, dissemination and use. Investigation process research and new data concepts behind the Semantic Web, exploited elsewhere, offer potential opportunities to overcome these impediments. To exploit these opportunities, formation of a working group to develop an improved Semantic Web-friendly mishap investigation lessons learning system is proposed. An example illustrating an alternative approach is described to support a reasonable expectation that an alternative lessons learning system could be developed.     

Research on flood risk analysis and evaluation method based on variable fuzzy sets and information diffusion

Floods have become increasingly alarming worldwide. Flood risk management in terms of assessing disaster risk properly is a great challenge that society faces today. Natural disaster risk analysis is typically beset with issues such as imprecision, uncertainty, and partial truth. There are two basic forms of uncertainty related to natural disaster risk assessment, namely, randomness caused by inherent stochastic variability and fuzziness due to macroscopic grad and incomplete knowledge sample. However, the traditional probability statistical method ignores the fuzziness of risk assessment with incomplete data sets and requires a large sample size of data. The fuzzy set methodology is introduced in the area of disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The present paper puts forward a composite method based on variable fuzzy sets and information diffusion method for disaster risk assessment. The results indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management. We hope that by conducting such risk analysis, the impact of flood disasters can be mitigated in the future.