Risk Evaluation: The Paradigm and Tools

Concept of a System Using a Dynamic SWOT Analysis Network for Fuzzy Control of Risk in Complex Environments

“…Terms corresponding to the ability of human beings to distinguish and evaluate not more than seven plus or minus two grades of qualitative difference are presented in Figure 3. The determination of the level of fuzzy risk concealed in a situation or project under consideration is based on our paradigmatic definition of risk presented in [9], and it constructively contradicts the opinion expressed in [10]. In this paper, risk is considered to be a normalized subjective level of the uncertainty of the consequences of activity and/or the state of the system of entities in complex environments.…”

“…It is worth of emphasizing here that all these components in Eq. (2) must be symbolically aggregated and/or summed, keeping in mind the corresponding truth values received from the fuzzy terms of their membership functions, as described and elaborated in [9]. During the summary process, SWOT experts must confront one of at least two cases: 1) when the degree of fuzzy membership is evaluated numerically (type 1 fuzzy relations) or 2) when the degree of fuzzy membership is evaluated verbally (type 2 fuzzy relations) ( [14]).…”

“…Results (6) and (7) ( a , a are comparable and can develop further consideration, but only after their normalization. It is obvious that this normalization can be achieved by involving coefficients of normalization (8) and (9) for threats and opportunities correspondingly: The remark positive means that only positive auxiliary flags are taken into account in all those sums as potentially capable to create maximal value of threats and possibilities according to (6) and (7). The coefficients for the normalization of (8) and (9) are determined after the analysis of (6) and (7), keeping in mind the fact that the maximal value of the summarized and normalized threat and of the summarized and normalized opportunity must not exceed 1.…”

“…The main kernel tool for verbal SWOT analysis, enriched by methodology of CWW (SWOT+CWW), was proposed and successfully developed in the Center of Real Time Computing Systems at Kaunas University of Technology (KTU) ( [8]). Many other tools are described in [9]. Other important fuzzy operations are described in [21 -23] together with the software used for their interactions.…”

“…This paper: 1) introduces and expands the dynamic approach to SWOT analysis as it was firstly proposed in [5] and [6], using the mechanism of dynamic fuzzy cognitive maps; 2) introduces the possibility of using quantitative and qualitative input and output data as well as to the verbal SWOT reasoning, using the paradigm of computing with words (CWW) as was firstly proposed for such procedure in [8]; 3) provides SWOT expert teams with the support tools for reasoning and decision making using fuzzy risk analysis, following the risk paradigm presented in [9], which methodologically corresponds to the conclusions provided in [7]. The definition, assessment, and management remains shaky and unfounded in general, so we selected and invented our own metrics for fuzzy risk with the aim of making them useful for decision makers in SWOT analysis.…”