Performance assessment system of health,safety and environment based on experts' weights and fuzzy comprehensive evaluation

Performance evaluation of Health, Safety and Environment (HSE) is the measurement of a company's achievement in HSE management. In order to receive a comprehensive and objective evaluation result, it is necessary to consider all evaluation factors and experts at different levels when HSE performance assessment is conducted. To improve conventional HSE performance evaluation, where weighted average method was used, a Fuzzy Comprehensive Evaluation (FCE) method is used in this study by taking experts' weights into account. Further, an HSE operating performance assessment system is designed to simplify manual and complex assessment process and generate charts and analysis reports automatically. Finally, a case of petrochemical enterprise is used to illustrate the effectiveness of the method and system.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

应用模糊综合指数法对伊犁河（伊宁段）水质的综合评价

模糊数学法对伊犁河(伊宁段)水质进行综合评价时,由于分别采用地面水环境质量标准中五类标准值的平均值及其中三个标准值,计算后的结果不一致,而模糊综合指数法避免了这类问题的出现,计算结果比较满意.从而表明,该法是对模糊数学法的进一步改进.     

基于AHP-MF模型的用户群节水指标体系研究

从分析影响用户群节水的因素及其构成关系入手,根据专家长期节水工作的经验,利用层次分析法对用户群节水指标进行优选,并提出全面的定量化和定性化的层次结构评价模式和总体评价方法.首先构建用户群节水的层次分析结构模型及判断矩阵,应用Matlab6.5计算出各判断矩阵的最大特征值及其特征向量,并检验判断矩阵的一致性,继而确定出各指标的权重;其次,应用Fuzzy统计的方法对陕西2006年度高校用户群的节水情况进行评价,并为节水工作提供建设性意见.     

城市大气污染物浓度预测模糊识别理论与模型

根据大气污染物的浓度具有模糊性且与多种指标相关的特点，提出对其进行预测的模糊识别理论与模型，并以二氧化硫为例，由２５个预测点大气中ＳＯ２浓度和相关指标的实测资料，利用上述理论与模型得出最优模糊预测参数，并对其它５个观测点的ＳＯ２浓度进行了预测检验。     

城市生活垃圾场处理技术模糊综合评价

通过对一个待建的城市生活垃圾场处理技术的综合分析，建立一个相对完整的指标体系，然后用模糊数学的方法，对指标体系进行量化、归一化，得到一个通用的评价模型，并运用此模型对该垃圾的垃圾处理方式进行评价，最后提出卫生填埋是当前较为合理的处理方式。     

湖泊水质富营养化评价的多准则神经网络法

提出了基于误差平方和准则与模糊熵准则下的多准则神经网络湖泊水质营养化评价模型，并将其应用于我国五大湖泊水质营养化的评价。结果表明，多准则神经网络用于湖泊水质营养化评价，具有简便，实用，客观和广泛的通用性     

除尘器优化选型的模糊数学模型

应用模糊数学和系统工程的原理和方法，对除尘器的优化选型进行了分析和研究，提出了一种除尘器优化选型的模糊数学模型，并对该模型的有效性和精确性进行了实例验证。