Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Baraldi, Piero; Librizzi, M.; Zio, Enrico; Podofillini, Luca; Dang, Vinh N.

doi:10.1016/j.eswa.2009.04.036

Cited by 22 publications

(5 citation statements)

References 10 publications

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“…Fuzzy Inference Systems (FIS) are popular computational frameworks and based on the concept of fuzzy sets. FISs are nonlinear systems designed of solve decision making and inference problems in uncertainty and assessment condition according to the rules that connect the input and output variables defined as If-Then (Baraldi et al 2009). The basic structures of FIS are composed of five conceptual parts (Haji, Assadi 2009): 1.…”

Section: Fuzzy Theorymentioning

confidence: 99%

Risk Assessment in Tourism System Using a Fuzzy Set and Dominance-Based Rough Set

Sabokbar

Ayashi

Hosseini

et al. 2016

Technological and Economic Development of Economy

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The purpose of this study is to identify risks, discover rule base structure and the impact of risks by knowledge base system design in one of the Iran tourism destination. Based on tourism system approach, the factors of risks are divided in two dimensions: internal risks and external risks and seven criteria: political, economic, cultural-social, technological, environmental-health, functional and safe-security. Data were analyzed by fuzzy inference system and Dominance-based Rough Set Approach (DRSA) synthesizing to construction of forecasting risk assessment system. Tourists’ perspectives towards the possibilities of risks were first assessed within seven risk factors and converted into a systematic structure within the structure of rough sets. Designing of a fuzzy expert system was dealt with using the created knowledge database. Then, the system’s sensitivity analysis was examined. The results indicate that the system can be a good way to estimate the risks and their fluctuation rates and impacts on the development of tourism destinations. The technological, social, functional and safety-security risks had the highest values in the system designed for minimum travel repeatability. The research suggests that it is important impact of risks and their interaction with each other on the future development of tourism destination.

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Section: Fuzzy Theorymentioning

confidence: 99%

Risk Assessment in Tourism System Using a Fuzzy Set and Dominance-Based Rough Set

Sabokbar

Ayashi

Hosseini

et al. 2016

Technological and Economic Development of Economy

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“…[28,59,69]), fuzzy logic, fuzzy networks (e.g. [4,13,43,62]), Bayesian theory (e.g. [14]), and Petri nets (e.g.…”

Section: The Uncertainty Problem In Decision Support Systems Developmentmentioning

confidence: 99%

Uncertainty Problem in Decision Support System for Means of Transport Maintenance Processes Performance Development / Problem Niepewności W Systemie Wsparcia Decyzyjnego Procesów Utrzymania W Stanie Zdatności Środków Transportu

Nowakowski¹,

Werbińska-Wojciechowska²

2012

Journal of KONBiN

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In this paper, the authors’ research work is focused on uncertainty analysis implementation in the developed DSS for transportation means’ maintenance processes performance. Thus, in the Introduction section, the transportation means’ maintenance processes issues and the uncertainty problem are described. Later, there is briefly literature overview in the research area discussed. In the next Section, the expert system for means of transport maintenance processes performance is also investigated. Following this, the uncertainty analysis is developed and the examples of expert system implementation are given. The work ends up with summary and directions for further research.

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“…Within a non-probabilistic framework, a fuzzy uncertainty importance measure (FUIM) has been proposed in Suresh et al 14 to identify those component level parameters q i having the greatest impact on the uncertainty of the system level parameter p. The FUIM measures the distance between the output fuzzy sets considering the input parameters q i with or without uncertainty. In Baraldi et al 31 the FUIM has been modified in order to consider the different imprecision in the output of the fuzzy sets, measured in terms of fuzzy specificity instead of the difference between the fuzzy sets. In Liping and Fuzheng, 16 an importance measure is proposed based on the concept of possibilistic entropy, which is then applied to fault tree analysis in a possibilistic framework.…”

Section: Introductionmentioning

confidence: 99%

An imprecision importance measure for uncertainty representations interpreted as lower and upper probabilities, with special emphasis on possibility theory

Flage

Aven

Baraldi

et al. 2012

Proceedings of the Institution of Mechanical Engineers, Part O:

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International audienceUncertainty importance measures typically reflect the degree to which uncertainty about risk and reliability parameters at the component level influences uncertainty about parameters at the system level. The definition of these measures is typically founded on a Bayesian perspective where subjective probabilities are used to express epistemic uncertainty; hence, they do not reflect the effect of imprecision in probability assignments, as captured by alternative uncertainty representation frameworks such as imprecise probability, possibility theory and evidence theory. In the present paper, we define an imprecision importance measure to evaluate the effect of removing imprecision to the extent that a probabilistic representation of uncertainty remains, as well as to the extent that no epistemic uncertainty remains. Possibility theory is highlighted throughout the paper as an example of an uncertainty representation reflecting imprecision, and used in particular in two numerical examples which are included for illustration

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Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Cited by 22 publications

References 10 publications

Risk Assessment in Tourism System Using a Fuzzy Set and Dominance-Based Rough Set

Risk Assessment in Tourism System Using a Fuzzy Set and Dominance-Based Rough Set

Uncertainty Problem in Decision Support System for Means of Transport Maintenance Processes Performance Development / Problem Niepewności W Systemie Wsparcia Decyzyjnego Procesów Utrzymania W Stanie Zdatności Środków Transportu

An imprecision importance measure for uncertainty representations interpreted as lower and upper probabilities, with special emphasis on possibility theory

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