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This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

The purpose of this paper is to propose a new analytical approach in human thought computation with an application to the child language acquisition research.

Certain fuzzy statistical concepts, such as fuzzy samples, fuzzy mode, fuzzy category test, and their relevant properties, were presented. Empirical data sets on children's language and cognitive development were discussed. Finally, the paper makes a comparison result between the traditional statistical analysis and fuzzy statistical analysis.

The results show that the new method is better able to capture the intricacies and complexities of the nature and processes in acquiring languages than the traditional methods.

The paper presents fuzzy statistical analysis as a new analytical approach in child language research.

The aim of this chapter is to review and illustrate a step-by-step guideline in conducting fuzzy-set Qualitative Comparative Analysis (fsQCA) in tourism and hospitality studies. As an emerging method, fsQCA is simultaneously quantitative and qualitative in nature which makes it an appropriate method for social science disciplines including tourism and hospitality area because of complex nature of relationships between multiple variables where theories and models are underdeveloped. Unlike conventional statistical techniques, fsQCA is an asymmetrical analysis technique that provides a holistic view and interrelationships among several conditions using Boolean algebra. The fsQCA analyses produce comprehensive assessment by revealing causal combinations of antecedents to predict an outcome; and identify sufficient configurations (i.e., causal combinations and recipes) and necessary condition/s. By utilizing this method, researchers would be able to produce complex, comprehensive, and robust results.

The purpose of this paper is to propose a new integrated method for evaluating inventory of slow-moving items by introducing the application of fuzzy AHP method with interval Type-2 fuzzy sets (IT2FSs) and ABC analysis.

In the study, fuzzy analytic hierarchy process (AHP) method with IT2FSs is employed to set the importance of criteria. The weights obtained from IT2 fuzzy AHP are used to classify slow-moving items in ABC analysis. In the application part, a real-life case study is presented.

The result of this study indicates that an integrated approach utilizing IT2 fuzzy AHP and ABC analysis can be used as a supportive tool for classification of slow-moving items. The problem is solved under fuzzy environment to handle uncertainties and lack of information about slow-moving items.

Actual data are provided from an automotive company for prioritizing a various criteria to evaluate and classify stocks and a hypothetical model integrated with IT2 fuzzy AHP and ABC analysis is demonstrated.

Apart from inventory classification literature, the study integrates fuzzy AHP method by employing interval IT2FSs and ABC analysis to solve the real-life inventory classification problem.

Prior reports on theory and research focusing on describing and explaining national cultural influences on purchase and consumption behavior use a net effects approach (i.e., theory and analysis relying on main and interaction effects via statistical analysis). Theory and research in this chapter advances qualitative comparative analysis (QCA) of a configuration perspective of culture's consequences on consumption behavior. This research informs the view that national cultures represent causal recipes (conjunctions) of cultural values; the study of main and interaction effects offer meager representations of national culture's consequences in comparison to adopting a cultural configuration stance. The configuration research here includes transforming Hofstede's country cultural scores into fuzzy set values and applying Boolean algebra to estimate the relevancy of alternative cultural configurations for each of 14 nations to consuming experiences during visits to Australia. The findings support primary and additional hypotheses that specific cultural configurations are sufficient (but not necessary) for describing substantial culture's consequences on consuming tourism experiences. For example, the animus (i.e., Carl Jung's unconscious masculine personality-force) configuration — the combination of high power (P), high individualism (I), high masculine (M), and low uncertainty avoidance (∼U) (i.e., P·I·M·∼U) — is sufficient in indicating not-shopping-for-gifts while visiting Australia. Western national cultures (e.g., United States) have higher fuzzy set scores than Eastern national cultures (e.g., Japan) for the animus configuration.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.

The purpose of this research is to develop a new approach for analyzing the fuzzy reliability of a series and parallel system. Also to introduce definition of L‐R type interval valued triangular vague set and certain Tω‐based arithmetic operations between two L‐R type interval valued triangular vague sets.

In the proposed approach using a fault tree an interval valued vague fault tree is developed for the system in which the fuzzy reliability of each component of the system is represented by a L‐R type interval valued triangular vague set. Then with the help of a developed interval valued vague fault tree an algorithm is developed to analyze the fuzzy system reliability.

For numerical verification of the proposed approach the fuzzy reliability of the basement flooding has been analyzed using the existing approaches and the proposed approach. Comparing the results of existing approaches and the proposed approach, it has been shown that the uncertainty about the reliability is minimized using the proposed approach and the results are exact. While using the existing approaches the results are approximate due to approximate product of triangular vague sets and interval valued triangular vague sets.

The paper introduces a new approach for analyzing the fuzzy system reliability using Tω‐based arithmetic operations over L‐R type interval valued triangular vague sets.

The aim of this chapter is to introduce a methodology that enables researchers to employ a set of systematic comparative tools and techniques in their multiple case study research that allow them to move from drawing loose comparisons towards a more formalised type of analysis, while simultaneously paying attention to within-case complexities. This methodology stands between the qualitative and the quantitative methods and helps researchers to build middle-range theories (Mjoset, 2001) from small to intermediate numbers of cases. This methodology encompasses a number of techniques including crisp and fuzzy set-theoretic qualitative comparative analyses, which have been used in a wide range of social science disciplines. However, these techniques have not received sufficient attention from higher education scholars.

Shalev's (2007) critique of the use of multiple regression in comparative research brings together and synthesizes a variety of previous critiques, ranging from those focusing on foundational issues (e.g., the persistent problem of limited diversity), to estimation issues (e.g., the unrealistic assumption of correct model specification), to narrow technical issues (e.g., the difficulty of deriving valid standard errors for regression coefficients in pooled cross-sectional time-series models). Broadly speaking, these concerns can be described as epistemological, theoretical, and methodological, respectively. While the distinctions among these three are not always clear-cut, the tripartite scheme provides a useful way to map the different kinds of critiques that may be directed at the use of regression analysis in comparative research. In the first half of this essay we build upon Shalev's discussion to clarify the conditions under which regression analysis may be epistemologically, theoretically, or methodologically inappropriate for comparative research. Our goal is to situate Shalev's specific critiques of the use of multiple regression in comparative work within the context of social research in general.

The purpose of this paper is to develop an effective treatment to analyze and diagnose urban rail transit (URT) vehicle maintenance strategy.

In this paper, the technique of Failure Mode and Effects Analysis (FMEA) is introduced into the examination of URT trains, first. Then the method of fuzzy-set-based assessment for FMEA is presented, which is the quantitative tool of Fuzzy-Set-based treatment for FMEA in analysis and diagnoses to URT maintenance strategy. Moreover, recommendations for further improvement of the proposed approach are also provided. Initial application into the vehicle maintenance of Shanghai URT System shows, that the proposed approach has a good performance and consequently is worth further development.

The paper presents a FMEA and fuzzy-set-based theoretical approach for analyzing and diagnosing current methods in URT vehicle maintenance strategy.

With rapid development of URT systems in the world especially in those highly populated areas, much more attentions are turning to researches on URT maintenance, nevertheless, few quantitative research achievement are mentioned or applied. This paper is a tentative attempt at introducing fuzzy-set theory into quantitative analysis and diagnoses of URT maintenance strategy.

The study in this paper is helpful in theory and practice of URT maintenance and its methodology could be further applied into a broad family of facility group or system in other engineering fields.