Evaluating Environmental Sustainability: An Integration of Multiple-Criteria Decision-Making and Fuzzy Logic

While pursuing economic development, countries around the world have become aware of the importance of environmental sustainability; therefore, the evaluation of environmental sustainability has become a significant issue. Traditionally, multiple-criteria decision-making (MCDM) was widely used as a way of evaluating environmental sustainability, Recently, several researchers have attempted to implement this evaluation with fuzzy logic since they recognized the assessment of environmental sustainability as a subjective judgment Intuition. This paper outlines a new evaluation-framework of environmental sustainability, which integrates fuzzy logic into MCDM. This evaluation-framework consists of 36 structured and 5 unstructured decision-points, wherein MCDM is used to handle the former and fuzzy logic serves for the latter, With the integrated evaluation-framework, the evaluations of environmental sustainability in 146 countries are calculated, ranked and clustered, and the evaluation results are very helpful to these countries, as they identify their obstacles towards environmental sustainability.     

Test case based risk predictions using artificial neural network

INTRODUCTION: The traditional fuzzy-rule-based risk assessment technique has been applied in many industries due to the capability of combining different parameters to obtain an overall risk. However, a drawback occurs as the technique is applied in circumstances where there are multiple parameters to be evaluated that are described by multiple linguistic terms. METHOD: In this study, a risk prediction model incorporating fuzzy set theory and Artificial Neural Network (ANN) capable of resolving the problem encountered is proposed. An algorithm capable of converting the risk-related parameters and the overall risk level from the fuzzy property to the crisp-valued attribute is also developed. Its application is demonstrated by a test case evaluating the navigational safety within port areas. RESULTS: It is concluded that a risk predicting ANN model is capable of generating reliable results as long as the training data takes into account any potential circumstance that may be met. IMPACT ON INDUSTRY: This paper provides safety assessment practitioners with a novel and flexible framework of modelling risks using a fuzzy-rule-base technique. It is especially applicable in circumstances where there are multiple parameters to be considered. The proposed framework also enables the port industry to manage navigational safety in a rational manner.     

Prioritizing highway safety improvement projects: A multi-criteria model and case study with SafetyAnalyst

This paper presents a multi-criteria model for prioritizing highway safety improvement projects, in which a set of criteria related to the project’s technical, economic, and social impacts are properly weighted in consideration. The proposed model features an Analytical Hierarchy Process (AHP) framework to tackle the multi-criteria decision making problem. Different from the conventional AHP, this paper adds a fuzzy scale level between the criteria level and the alternative level, which offers the advantage of preventing the vagueness and uncertainty on judgments of the decision-maker(s). Such a unique modeling feature is further embedded with a non-linear optimization formulation to maximize the consistency in pair-wise comparison and weight estimation for each criterion. Case study results reveal that the proposed model is efficient not only for selecting the most suitable project for a specific site, but also for determining the priorities for implementing those suitable projects among multiple sites given the budget constraint. Comparative study between the proposed model and the existing ranking methods has also indicated its capability to capture the comprehensive impacts of all contributory factors which have been neglected by most existing single multi-criteria approaches during the safety project selection process. The clarity of model inputs, ease of synthesizing the final score of each candidate project, and the interpretation of results with respect to different selection criteria offer its best potential to be used as an effective tool for highway safety managers to assess and refine the safety improvement investments.     

Risk assessment of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree

The oxygen-enhanced combustor has the advantages of high burning efficiency and low emissions. However, it should not be promoted for industrial use until its reliability and safety have been fully recognized. A new methodology is proposed to assess the risk of an oxygen-enhanced combustor using a structural model based on the FMEA and fuzzy fault tree. In addition, it is applied to a selected pilot semi-industrial combustor. To identify the hazard source comprehensively, the pilot is divided into four subsystems: the combustor subsystem, feed subsystem, ignition subsystem and exhaust subsystem. According to the operational parameters of flow (flow rate, temperature and pressure) and the component functions in different subsystems, the cause and effect matrix can be built using the structural model, and the relationship between the operational parameters and the effects of the change for the operational parameters on the system can be presented. Based on the results of cause and effect matrix, the FMEA can be built to describe the failed models and accident scenarios of the pilot. The main accident forms include leakage, injury, fire and explosion. Accordingly, with the severity and probability analysis of different accident forms, the fire and explosion accidents should be further accessed quantitatively using the fuzzy fault tree analysis. The fault trees can be obtained in accordance with the FMEA, and the qualitative assessments of the basic events can be collected by using expert scoring. A hybrid approach for the fuzzy set theory and weight analysis is investigated to quantify the occurrence probability of basic events. Then, the importance analysis of the fault trees, including the hazard importance of basic events and the cut set importance, is performed to help determine the weak links of the fire and explosion trees. Finally, some of the most effective measures are presented to improve the reliability and safety of the combustion system.     

红枫湖富营养化模糊评价

以红枫湖为例,论述水体富营养化模糊综合评价过程。结果表明,红枫湖属于中营养化,富营养化趋势得到遏制;证明模糊评价法应用于水体富营养化评价是可行的;揭示湖泊富营养化评价应结合多种方法进行研究,使评价结果更趋于合理。     

Fuzzy risk assessment of oil and gas offshore wells

Risk evaluation of offshore wells is a challenging task, given that much of the available data is highly uncertain and vague, and many of the mechanisms are complex and difficult to understand. Consequently, a systematic approach is required to handle both quantitative and qualitative data as well as means to update existing information when new knowledge and data become available. Each Basic Risk Item (BRI) in a hierarchical framework is expressed as a fuzzy number, which is a combination of the likelihood of a failure event and the associated failure consequence. Analytical Hierarchy Process (AHP) is used to estimate weights required for grouping non-commensurate risk sources. Evidential Reasoning (ER) is employed to incorporate new data for updating existing risk estimates. It is envisaged that the proposed approach could serve as a basis for benchmarking acceptable risks in offshore wells.     

基于模糊综合评判的贵州省水资源安全评价研究

为了准确把握目前贵州省水资源安全所处状态,文章从综合效益、水资源利用效率、水资源保护、管理水平、水资源可持续性5个方面23个指标建立了评价体系,并利用模糊综合评判方法,对贵州省水资源安全进行了综合评价。评价结果表明,贵州省现阶段水资源安全状态处在亚安全等级,综合效益不高、水资源利用效率低下以及水资源管理水平落后等因素制约了全省水资源的可持续发展。     

应用模糊数学法综合评价丹东铁甲水库水质级别

应用模糊数学法,综合5项主要污染指标,评价了2008-2012年丹东铁甲水库的水质级别,改变了仅凭单因子评价水质级别的方法,评价更合理,更符合实际情况。     

Integration of fuzzy reliability analysis and consequence simulation to conduct risk assessment

Losses of containment within the natural gas network, located in most populated areas, could cause environmental damage, injuries, or even death. Accordingly, it is pivotal to adopt proper approaches to assess and mitigate the risk arising from potential losses. Within this context, it is required to exploit solid reliability and consequence analysis techniques. To this end, this paper presents a methodology established on the integration of a Fuzzy Bayesian Network and consequence simulation. The Bayesian Network is more flexible and realistic than classic approaches because it can consider conditional probabilities and prior information. Furthermore, Leaky Noisy-OR Gates are exploited to allow an easier filling of the Conditional Probability Tables. This task is performed through expert elicitation, adopting Intuitionistic Fuzzy Set Theory and Similarity Aggregation Method. Finally, the severity analysis is performed via a software, named Safeti, which provides an accurate evaluation of the consequences. To show the applicability of the framework, a pressure regulator of a Natural Gas Regulating and Metering Station is considered as case study. The proposed approach can assist asset managers in evaluating the risk arising from the operations, and, accordingly, it can guide them in making maintenance-related decisions to assure the safety of the operations.     

Fuzzy Logic Model for the performance benchmarking of sugar plants by considering best available techniques

This paper deals with the problem of performance benchmarking of traditional beet sugar plants, by considering Best Available Techniques (BAT) for beet sugar production, as determined by the Integrated Pollution Prevention and Control (IPPC) Directive. A Fuzzy Logic Model, based on fuzzy set theory, was constructed for this purpose, in order to compare the performances of sugar plants within the sector's best standards, as expressed in the Reference Document on BAT.The effectiveness of the model was tested in the case study, in which three sugar plants were benchmarked against the BAT regarding the consumption of energy, water, raw materials and the production of wastes, wastewater, by-products and the main product. The model was recognized as helpful for the benchmarking needs of sugar plants. In addition, by integrating BAT Reference Document analysis into the model, it provides IPPC permitting authorities with an objective method and uniform BAT benchmarks to manage permitting process.