A Linguistic-Valued Information Processing Method for Fuzzy Risk Analysis

Abstract

Risk analysis is a crucial issue to be handled in disaster management. Fuzzy risk analysis, i.e., risk analysis model using fuzzy set theory aims to assess the risk of hazard event under incomplete or imprecise environment. In practice, the evaluations of risk is always expressed by linguistic values in natural language. In this chapter, we present two approaches for fuzzy risk analysis with linguistic evaluation values. The first approach is based on the unbalanced linguistic weighted geometric operator, which can be used to deal with aggregation of unbalanced linguistic risk evaluation values with numerical weights or linguistic weights. The advantage of the approach is that the evaluation result is linguistic value which is no need of approximation processing and easier to communicate to decision and policy-makers. The other approach is based on linguistic truth-values lattice implication algebra from the logical algebraic point of view. We discuss the operations and special properties of the lattice implication algebra with evaluation-10 linguistic evaluation values. The reasoning and aggregation process directly act on the linguistic evaluation values in the risk analysis process. This approach can better express and handle both comparable and incomparable linguistic information in risk analysis domains. The proposed approaches aim at provide a support for risk analysis in different application context including disaster management under uncertain environment.